GAMMs analyses Trombone - Tongan vs English (NZE) -> Plots

This notebook provides some plots for the article: Heyne, M., Derrick, D., and Al-Tamimi, J. (under review). “Native language influence on brass instrument performance: An application of generalized additive mixed models (GAMMs) to midsagittal ultrasound images of the tongue”. Frontiers Research Topic: Models and Theories of Speech Production. Ed. Adamantios Gafos & Pascal van Lieshout.

1 Loading packages

load_packages = c("readr","knitr","ggplot2","mgcv","itsadug","parallel","dplyr","rlist","plotly")
# dplyr, rlist, and plotly are required by the custom plotting functions
for(pkg in load_packages){
  eval(bquote(library(.(pkg))))
  if (paste0("package:", pkg) %in% search()){
    cat(paste0("Successfully loaded the ", pkg, " package.\n"))
  }else{
    install.packages(pkg)
    eval(bquote(library(.(pkg))))
    if (paste0("package:", pkg) %in% search()){
      cat(paste0("Successfully loaded the ", pkg, " package.\n"))
    }
  }
}

Successfully loaded the readr package.
Successfully loaded the knitr package.
Successfully loaded the ggplot2 package.
Successfully loaded the mgcv package.
Successfully loaded the itsadug package.
Successfully loaded the parallel package.
Successfully loaded the dplyr package.
Successfully loaded the rlist package.
Successfully loaded the plotly package.

rm(load_packages, pkg)
# detect number of cores available for model calculations
ncores = detectCores()
cat(paste0("Number of cores available for model calculations set to ", ncores, "."))

Number of cores available for model calculations set to 8.

1.1 Loading custom plotting function

1.2 plotly_sig_diff_notes function (Matthias Heyne, 2019)

# plot smooths with shading to indicate significant differences (Matthias Heyne, 2019)
plotly_smooths_w_sig_diff <- function(model, condition, var1, var2, values, language, print=TRUE){
  # specify path for saving plots
  # plot_folder = "saved_plots"
  # Sys.setenv(MAPBOX_TOKEN = 11122223333444)
  # get intervals of significant differences by running plot_diff
  # unfortunately setting plot=FALSE doesn't work as intervals of significant difference are not displayed!
  # hardcoded condition
  # output = capture.output(plot_diff(get(model), view=values, 
  #                                   comp=list(tokenPooled.ord=c(var1, var2))))
  # output = capture.output(plot_diff(get(model), view=values, comp=list(langNoteInt.ord=c(paste0("Tongan.", note, ".", intensity), paste0("NZE.", note, ".", intensity)))))
  names_smooths=list()
  if (condition=="tokenPooled.ord" && length(language)==1){
    output_comp = capture.output(cat(paste0("list(", condition, "=c(var1, var2))")))
    names_smooths[1]=var1
    names_smooths[2]=var2
    plot_title = paste0("GAM smooths ", language, " ", var1, " vs ", var2)
    # plot_filename = paste0(language, "_", var1, "_vs_", var2, "_from_", model)
  }else if (condition=="langNoteInt.ord" && length(language)==2){
    output_comp = capture.output(cat(paste0("list(", condition, "=c('", language[1], ".", var1, ".", var2, 
                                            "', '", language[2], ".", var1, ".", var2, "'))")))
    names_smooths[1]=paste0(language[1], ".", var1, ".", var2)
    names_smooths[2]=paste0(language[2], ".", var1, ".", var2)
    plot_title = paste0("GAM smooths ", language[1], ".", var1, ".", var2, " vs ", language[2], ".", var1, ".", var2)
    # plot_filename = paste0(language[1], ".", var1, ".", var2, "_vs_", language[2], ".", var1, ".", var2, "_from_", model)
  }else if (condition=="langNoteInt.ord" && length(language)==1 && length(var1)==2){
    output_comp = capture.output(cat(paste0("list(", condition, "=c('", language, ".", var1[1], ".", var2, 
                                            "', '", language, ".", var1[2], ".", var2, "'))")))
    names_smooths[1]=paste0(language, ".", var1[1], ".", var2)
    names_smooths[2]=paste0(language, ".", var1[2], ".", var2)
    plot_title = paste0("GAM smooths ", language, ".", var1[1], ".", var2, " vs ", language, ".", var1[2], ".", var2)
    # plot_filename = paste0(language, ".", var1[1], ".", var2, "_vs_", language, ".", var1[2], ".", var2, "_from_", model)
  }
  # output_comp = capture.output(cat(paste0("list(", condition, "=c(var1, var2))")))
  output = capture.output(plot_diff(get(model), view=values, comp=eval(parse(text=output_comp))))
  # no significant difference
  if ((length(language)==1 && length(var1)==1 && length(output)==7) | (length(language)==2 && length(output)==6) | 
    (length(language)==1 && length(var1)==2 && length(output)==6)){
    if (length(var1)==1){
      cat(paste0("Smooths for ", var1, " & ", var2, " are not significantly different.\n"))
      dat1 = NA
      assign(paste0("int_sig_diff_", var1, "_", var2), dat1, envir = .GlobalEnv)
    }else{
      cat(paste0("Smooths for ", var1[1], " & ", var1[2], " in ", language, " are not significantly different.\n"))
      dat1 = NA
      assign(paste0("int_sig_diff_", var1[1], "_", var1[2], "_", var2, "_", language), dat1, envir = .GlobalEnv)
    }
    rm(dat1, output)
    # run plot_smooth to grab data for polar plots
    if (condition=="tokenPooled.ord" && length(language)==1){
      cond_p1 = capture.output(cat(paste0("list(", condition, "=var1)")))
      cond_p2 = capture.output(cat(paste0("list(", condition, "=var2)")))
    }else if (condition=="langNoteInt.ord" && length(language)==2){
      cond_p1 = capture.output(cat(paste0("list(", condition, "='", language[1], ".", var1, ".", var2, 
                                          "', ", condition, "='", language[2], ".", var1, ".", var2, "')")))
      cond_p2 = capture.output(cat(paste0("list(", condition, "='", language[2], ".", var1, ".", var2, 
                                          "', ", condition, "='", language[1], ".", var1, ".", var2, "')")))
    }else if (condition=="langNoteInt.ord" && length(language)==1 && length(var1)==2){
      cond_p1 = capture.output(cat(paste0("list(", condition, "='", language, ".", var1[1], ".", var2, 
                                          "', ", condition, "='", language, ".", var1[2], ".", var2, "')")))
      cond_p2 = capture.output(cat(paste0("list(", condition, "='", language, ".", var1[2], ".", var2, 
                                          "', ", condition, "='", language, ".", var1[1], ".", var2, "')")))
    }
    p1 = plot_smooth(x=get(model), view=values, cond=eval(parse(text=cond_p1)), rm.ranef=TRUE)
    p2 = plot_smooth(x=get(model), view=values, cond=eval(parse(text=cond_p2)), rm.ranef=TRUE)
    # # old - hardcoded
    # p1 = plot_smooth(x=get(model), view=values, cond=list(tokenPooled.ord=var1, tokenPooled.ord=var2))
    # p2 = plot_smooth(x=get(model), view=values, cond=list(tokenPooled.ord=var2, tokenPooled.ord=var1))
    # set Rho max to the max of the fit + half the difference between max of the fit and the upper limit
    maximum=max(p1$fv$fit, p2$fv$fit)+((max(p1$fv$ul, p2$fv$ul)-max(p1$fv$fit, p2$fv$fit))/2)
    # plot in polar coordinates
    p=plot_ly(type='scatterpolar', mode='lines') %>% 
      add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color="blue", dash="dash", width=2.5), name=names_smooths[1]) %>% 
      add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
      add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color="blue", dash="dash",  width=0.5), showlegend=FALSE) %>% 
      add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color="red", width=2.5), name=names_smooths[2]) %>% 
      add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>% 
      add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>%
      layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                        angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
             title=paste0("GAM smooths ", language, " ", var1, " vs ", var2), 
             legend=list(orientation="h", xanchor="center", x=0.5))
    Sys.sleep(0)
    print(p)
  # there are differences...
  }else{
    # grab intervals of significant differences from output
    if (length(language)==1 && length(var1)==1 && length(output)>=8){
    # if (length(language)==1 && length(output)>=8){
      sig_diff1 = c(as.double(unlist(strsplit(unlist(strsplit(output[8], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[8], " "))[3]))
    }else if ((length(language)==2 && length(output)>=7) | (length(language)==1 && length(var1)==2 && length(output)>=7)){
    # }else if (length(language)==2 && length(output)>=7){
      sig_diff1 = c(as.double(unlist(strsplit(unlist(strsplit(output[7], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[7], " "))[3]))
    }
    if (length(language)==1 && length(var1)==1 && length(output)>=9){
    # if (length(language)==1 && length(output)>=9){
      sig_diff2 = c(as.double(unlist(strsplit(unlist(strsplit(output[9], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[9], " "))[3]))
    }else if ((length(language)==2 && length(output)>=8) | (length(language)==1 && length(var1)==2 && length(output)>=8)){
    # }else if (length(language)==2 && length(output)>=8){
      sig_diff2 = c(as.double(unlist(strsplit(unlist(strsplit(output[8], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[8], " "))[3]))
    }
    if (length(language)==1 && length(var1)==1 && length(output)>=10){
    # if (length(language)==1 && length(output)>=10){
      sig_diff3 = c(as.double(unlist(strsplit(unlist(strsplit(output[10], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[10], " "))[3]))
    }else if ((length(language)==2 && length(output)>=9) | (length(language)==1 && length(var1)==2 && length(output)>=9)){
    # }else if (length(language)==2 && length(output)>=9){
      sig_diff3 = c(as.double(unlist(strsplit(unlist(strsplit(output[9], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[9], " "))[3]))
    }
    if (length(language)==1 && length(var1)==1 && length(output)>=11){
    # if (length(language)==1 && length(output)>=11){
      sig_diff4 = c(as.double(unlist(strsplit(unlist(strsplit(output[11], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[11], " "))[3]))
    }else if ((length(language)==2 && length(output)>=10) | (length(language)==1 && length(var1)==2 && length(output)>=10)){
    # }else if (length(language)==2 && length(output)>=10){
      sig_diff4 = c(as.double(unlist(strsplit(unlist(strsplit(output[10], " "))[1], "\t"))[2]), as.double(unlist(strsplit(output[10], " "))[3]))
    }
    
    # write intervals of significant difference to variable
    if ((length(language)==1 && length(var1)==1 && length(output)>=11) | ((length(language)==2 && length(output)>=10)) | 
        (length(language)==1 && length(var1)==2 && length(output)>=10)){
    # if ((length(language)==1 && length(output)>=11) | (length(language)==2 && length(output)>=10)){
      dat1 = c(sig_diff1, sig_diff2, sig_diff3, sig_diff4)
    }else if ((length(language)==1 && length(var1)==1 && length(output)>=10) | ((length(language)==2 && length(output)>=9)) | 
              (length(language)==1 && length(var1)==2 && length(output)>=9)){
    # }else if ((length(language)==1 && length(output)>=10) | (length(language)==2 && length(output)>=9)){
      dat1 = c(sig_diff1, sig_diff2, sig_diff3)
    }else if ((length(language)==1 && length(var1)==1 && length(output)>=9) | ((length(language)==2 && length(output)>=8)) | 
              (length(language)==1 && length(var1)==2 && length(output)>=8)){
    # }else if ((length(language)==1 && length(output)>=9) | (length(language)==2 && length(output)>=8)){
      dat1 = c(sig_diff1, sig_diff2)
    }else{
      dat1 = sig_diff1
    }
    # old
    # assign(paste0("int_sig_diff_", var1, "_", var2), dat1, envir = .GlobalEnv)
    if (length(var1)==1){
      assign(paste0("int_sig_diff_", var1, "_", var2), dat1, envir = .GlobalEnv)
    }else{
      assign(paste0("int_sig_diff_", var1[1], "_", var1[2], "_", var2, "_", language), dat1, envir = .GlobalEnv)
    }
    rm(dat1, output)
    # run plot_smooth to grab data for polar plots
    if (condition=="tokenPooled.ord" && length(language)==1){
      cond_p1 = capture.output(cat(paste0("list(", condition, "=var1)")))
      cond_p2 = capture.output(cat(paste0("list(", condition, "=var2)")))
    }else if (condition=="langNoteInt.ord" && length(language)==2){
      cond_p1 = capture.output(cat(paste0("list(", condition, "='", language[1], ".", var1, ".", var2, 
                                "', ", condition, "='", language[2], ".", var1, ".", var2, "')")))
      cond_p2 = capture.output(cat(paste0("list(", condition, "='", language[2], ".", var1, ".", var2, 
                                          "', ", condition, "='", language[1], ".", var1, ".", var2, "')")))
    }else if (condition=="langNoteInt.ord" && length(language)==1 && length(var1)==2){
      cond_p1 = capture.output(cat(paste0("list(", condition, "='", language, ".", var1[1], ".", var2, 
                                          "', ", condition, "='", language, ".", var1[2], ".", var2, "')")))
      cond_p2 = capture.output(cat(paste0("list(", condition, "='", language, ".", var1[2], ".", var2, 
                                          "', ", condition, "='", language, ".", var1[1], ".", var2, "')")))
    }
    p1 = plot_smooth(x=get(model), view=values, cond=eval(parse(text=cond_p1)), rm.ranef=TRUE)
    p2 = plot_smooth(x=get(model), view=values, cond=eval(parse(text=cond_p2)), rm.ranef=TRUE)
    # set Rho max to the max of the fit + half the difference between max of the fit and the upper limit
    maximum=max(p1$fv$fit, p2$fv$fit)+((max(p1$fv$ul, p2$fv$ul)-max(p1$fv$fit, p2$fv$fit))/2)
    # plot in polar coordinates
    if (exists("sig_diff4")){
      p=plot_ly(type='scatterpolar', mode='lines') %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color="blue", dash="dash", width=2.5), name=names_smooths[1]) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color="red", width=2.5), name=names_smooths[2]) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff1[1]*180/pi, sig_diff1[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff2[1]*180/pi, sig_diff2[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff3[1]*180/pi, sig_diff3[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff4[1]*180/pi, sig_diff4[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                          angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
               title=plot_title, legend=list(orientation="h", xanchor="center", x=0.5))
      Sys.sleep(0)
      print(p)
    }else if (exists("sig_diff3")){
      p=plot_ly(type='scatterpolar', mode='lines') %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color="blue", dash="dash", width=2.5), name=names_smooths[1]) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color="red", width=2.5), name=names_smooths[2]) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff1[1]*180/pi, sig_diff1[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff2[1]*180/pi, sig_diff2[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff3[1]*180/pi, sig_diff3[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                          angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
               title=plot_title, legend=list(orientation="h", xanchor="center", x=0.5))
      Sys.sleep(0)
      print(p)
    }else if (exists("sig_diff2")){
      p=plot_ly(type='scatterpolar', mode='lines') %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color="blue", dash="dash", width=2.5), name=names_smooths[1]) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color="red", width=2.5), name=names_smooths[2]) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff1[1]*180/pi, sig_diff1[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff2[1]*180/pi, sig_diff2[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                          angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
               title=plot_title, legend=list(orientation="h", xanchor="center", x=0.5))
      Sys.sleep(0)
      print(p)
    }else{
      p=plot_ly(type='scatterpolar', mode='lines') %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color="blue", dash="dash", width=2.5), name=names_smooths[1]) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color="blue", dash="dash", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color="red", width=2.5), name=names_smooths[2]) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>% 
        add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color="red", dash="dot", width=0.5), showlegend=FALSE) %>%
        add_trace(theta=seq(sig_diff1[1]*180/pi, sig_diff1[2]*180/pi, length.out=20), 
                  r=c(0, rep(maximum, 18), 0), line=list(color="black", width=0.5), fill="toself", fillcolor=rgb(0,0,0,max=255,alpha=25), showlegend=FALSE) %>%
        layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                          angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
               title=plot_title, legend=list(orientation="h", xanchor="center", x=0.5))
      Sys.sleep(0)
      print(p)
    }
  }
  # orca should work with plotly 4.9.0 after loading the orca module before stating R and RStudio
  # orca(p, "test.pdf")
}

# load final model for H2 NZE
NZE.gam.AR.Mod2 = readRDS("updated_models/NZE.gam.AR.Mod2.rds")

2 Plot final model outputs: NZE.gam.AR.Mod2

2.1 Vowel “ɐː”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ɐː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ɐː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ɐː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ɐː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ɐː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.2 Vowel “ɐ”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ɐ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ɐ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ɐ", values="theta_uncut_z", language="NZE")

Smooths for Bb3 & ɐ are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ɐ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ɐ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.3 Vowel “ɛ”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ɛ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɛ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ɛ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɛ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ɛ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɛ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ɛ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɛ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ɛ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɛ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.4 Vowel “ɵː”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ɵː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɵː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ɵː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɵː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ɵː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɵː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ɵː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɵː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ɵː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɵː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.5 Vowel “e”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="e", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="e", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="e", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="e", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="e", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.6 Vowel “iː”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="iː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): iː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="iː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): iː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="iː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): iː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="iː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): iː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="iː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): iː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.7 Vowel “ʉː”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ʉː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʉː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ʉː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʉː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ʉː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʉː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ʉː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʉː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ʉː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʉː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.8 Vowel “ʊ”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ʊ", values="theta_uncut_z", language="NZE")

Smooths for Bb2 & ʊ are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʊ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ʊ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʊ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ʊ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʊ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ʊ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʊ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ʊ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʊ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.9 Vowel “oː”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="oː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): oː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="oː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): oː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="oː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): oː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="oː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): oː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="oː", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): oː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.10 Vowel “ɒ”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ɒ", values="theta_uncut_z", language="NZE")

Smooths for Bb2 & ɒ are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ɒ", values="theta_uncut_z", language="NZE")

Smooths for F3 & ɒ are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ɒ", values="theta_uncut_z", language="NZE")

Smooths for Bb3 & ɒ are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ɒ", values="theta_uncut_z", language="NZE")

Smooths for D4 & ɒ are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ɒ", values="theta_uncut_z", language="NZE")

Smooths for F4 & ɒ are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.11 Vowel “ɘ”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ɘ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɘ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ɘ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɘ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ɘ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɘ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ɘ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɘ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ɘ", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɘ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.12 Vowel “ə”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ə", values="theta_uncut_z", language="NZE")

Smooths for Bb2 & ə are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ə", values="theta_uncut_z", language="NZE")

Smooths for F3 & ə are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ə", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ə", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ə", values="theta_uncut_z", language="NZE")

Smooths for F4 & ə are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

2.13 Vowel “ə#”

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="ə#", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="ə#", values="theta_uncut_z", language="NZE")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="ə#", values="theta_uncut_z", language="NZE")

Smooths for Bb3 & ə# are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="ə#", values="theta_uncut_z", language="NZE")

Smooths for D4 & ə# are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="NZE.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="ə#", values="theta_uncut_z", language="NZE")

Smooths for F4 & ə# are not significantly different.
Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

# combine int_sig_diff... from workspace
all_sig_diff_intervals = (list=ls(pattern="^int_sig_diff"))
max_sig_diff_intervals = 0
for (i in 1:length(all_sig_diff_intervals)){
  if (length(get(all_sig_diff_intervals[i]))>max_sig_diff_intervals){
    max_sig_diff_intervals = length(get(all_sig_diff_intervals[i]))
  }
}
# set up data.frame to store information
sig_diffs = array(NA, c(length(all_sig_diff_intervals), max_sig_diff_intervals))
sig_diffs = data.frame(sig_diffs)
if (max_sig_diff_intervals==8){
  colnames(sig_diffs) = c("low_int1","high_int1","low_int2","high_int2",
                          "low_int3","high_int3","low_int4","high_int4")
}else if (max_sig_diff_intervals==6){
  colnames(sig_diffs) = c("low_int1","high_int1","low_int2","high_int2","low_int3","high_int3")
}else if (max_sig_diff_intervals==4){
  colnames(sig_diffs) = c("low_int1","high_int1","low_int2","high_int2")
}else{
  colnames(sig_diffs) = c("low_int1","high_int1")
}
# create empty list for row names
names = rep(list("NA"), length(all_sig_diff_intervals))
# loop through variable and write information to data.frame
for (i in 1:length(all_sig_diff_intervals)){
  names[i] = paste0(unlist(strsplit(all_sig_diff_intervals[i], "_"))[4], "_",
                    unlist(strsplit(all_sig_diff_intervals[i], "_"))[5])
  sig_diffs[i, 1] = get(all_sig_diff_intervals[i])[1]
  sig_diffs[i, 2] = get(all_sig_diff_intervals[i])[2]
  if (length(get(all_sig_diff_intervals[i]))>=4){
    sig_diffs[i, 3] = get(all_sig_diff_intervals[i])[3]
    sig_diffs[i, 4] = get(all_sig_diff_intervals[i])[4]
  }
  if (length(get(all_sig_diff_intervals[i]))>=6){
    sig_diffs[i, 5] = get(all_sig_diff_intervals[i])[5]
    sig_diffs[i, 6] = get(all_sig_diff_intervals[i])[6]
  }
  if (length(get(all_sig_diff_intervals[i]))==8){
    sig_diffs[i, 7] = get(all_sig_diff_intervals[i])[7]
    sig_diffs[i, 8] = get(all_sig_diff_intervals[i])[8]
  }
}
row.names(sig_diffs) = names
rm(i)
# inspect sig_diffs data.frame and move entries for conditions with only 
# one significantly different interval to other edge, if applicable
sig_diffs["Bb2_ɐ",5] = sig_diffs["Bb2_ɐ",1]
sig_diffs["Bb2_ɐ",6] = sig_diffs["Bb2_ɐ",2]
sig_diffs["Bb2_ɐ",1:2] = NA
sig_diffs["Bb2_ɐː",5] = sig_diffs["Bb2_ɐː",1]
sig_diffs["Bb2_ɐː",6] = sig_diffs["Bb2_ɐː",2]
sig_diffs["Bb2_ɐː",1:2] = NA
sig_diffs["Bb2_e",5] = sig_diffs["Bb2_e",3]
sig_diffs["Bb2_e",6] = sig_diffs["Bb2_e",4]
sig_diffs["Bb2_e",3:4] = NA
sig_diffs["Bb2_ə#",5] = sig_diffs["Bb2_ə#",1]
sig_diffs["Bb2_ə#",6] = sig_diffs["Bb2_ə#",2]
sig_diffs["Bb2_ə#",1:2] = NA
sig_diffs["Bb2_ɛ",5] = sig_diffs["Bb2_ɛ",1]
sig_diffs["Bb2_ɛ",6] = sig_diffs["Bb2_ɛ",2]
sig_diffs["Bb2_ɛ",1:2] = NA
sig_diffs["Bb2_ɘ",5] = sig_diffs["Bb2_ɘ",1]
sig_diffs["Bb2_ɘ",6] = sig_diffs["Bb2_ɘ",2]
sig_diffs["Bb2_ɘ",1:2] = NA
sig_diffs["Bb2_oː",5] = sig_diffs["Bb2_oː",3]
sig_diffs["Bb2_oː",6] = sig_diffs["Bb2_oː",4]
sig_diffs["Bb2_oː",3:4] = NA
sig_diffs["Bb2_oː",3] = sig_diffs["Bb2_oː",1]
sig_diffs["Bb2_oː",4] = sig_diffs["Bb2_oː",2]
sig_diffs["Bb2_oː",1:2] = NA
sig_diffs["Bb2_ɵː",5] = sig_diffs["Bb2_ɵː",3]
sig_diffs["Bb2_ɵː",6] = sig_diffs["Bb2_ɵː",4]
sig_diffs["Bb2_ɵː",3:4] = NA
sig_diffs["Bb3_ɛ",5] = sig_diffs["Bb3_ɛ",3]
sig_diffs["Bb3_ɛ",6] = sig_diffs["Bb3_ɛ",4]
sig_diffs["Bb3_ɛ",3:4] = NA
sig_diffs["Bb3_oː",5] = sig_diffs["Bb3_oː",3]
sig_diffs["Bb3_oː",6] = sig_diffs["Bb3_oː",4]
sig_diffs["Bb3_oː",3:4] = NA
sig_diffs["D4_ɐ",5] = sig_diffs["D4_ɐ",3]
sig_diffs["D4_ɐ",6] = sig_diffs["D4_ɐ",4]
sig_diffs["D4_ɐ",3:4] = NA
sig_diffs["D4_ɐː",5] = sig_diffs["D4_ɐː",3]
sig_diffs["D4_ɐː",6] = sig_diffs["D4_ɐː",4]
sig_diffs["D4_ɐː",3:4] = NA
sig_diffs["D4_oː",5] = sig_diffs["D4_oː",3]
sig_diffs["D4_oː",6] = sig_diffs["D4_oː",4]
sig_diffs["D4_oː",3:4] = NA
sig_diffs["F3_ɐ",5] = sig_diffs["F3_ɐ",1]
sig_diffs["F3_ɐ",6] = sig_diffs["F3_ɐ",2]
sig_diffs["F3_ɐ",1:2] = NA
sig_diffs["F3_ɐː",5] = sig_diffs["F3_ɐː",1]
sig_diffs["F3_ɐː",6] = sig_diffs["F3_ɐː",2]
sig_diffs["F3_ɐː",1:2] = NA
sig_diffs["F3_ə#",5] = sig_diffs["F3_ə#",1]
sig_diffs["F3_ə#",6] = sig_diffs["F3_ə#",2]
sig_diffs["F3_ə#",1:2] = NA
sig_diffs["F3_ɛ",5] = sig_diffs["F3_ɛ",3]
sig_diffs["F3_ɛ",6] = sig_diffs["F3_ɛ",4]
sig_diffs["F3_ɛ",3:4] = NA
sig_diffs["F3_ɘ",5] = sig_diffs["F3_ɘ",3]
sig_diffs["F3_ɘ",6] = sig_diffs["F3_ɘ",4]
sig_diffs["F3_ɘ",3:4] = NA
sig_diffs["F3_oː",5] = sig_diffs["F3_oː",3]
sig_diffs["F3_oː",6] = sig_diffs["F3_oː",4]
sig_diffs["F3_oː",3:4] = NA
sig_diffs["F3_ɵː",5] = sig_diffs["F3_ɵː",3]
sig_diffs["F3_ɵː",6] = sig_diffs["F3_ɵː",4]
sig_diffs["F3_ɵː",3:4] = NA
sig_diffs["F4_ɐ",5] = sig_diffs["F4_ɐ",1]
sig_diffs["F4_ɐ",6] = sig_diffs["F4_ɐ",2]
sig_diffs["F4_ɐ",1:2] = NA
sig_diffs["F4_ɐː",5] = sig_diffs["F4_ɐː",1]
sig_diffs["F4_ɐː",6] = sig_diffs["F4_ɐː",2]
sig_diffs["F4_ɐː",1:2] = NA
sig_diffs["F4_ɛ",5] = sig_diffs["F4_ɛ",3]
sig_diffs["F4_ɛ",6] = sig_diffs["F4_ɛ",4]
sig_diffs["F4_ɛ",3:4] = NA
sig_diffs["F4_ɘ",5] = sig_diffs["F4_ɘ",3]
sig_diffs["F4_ɘ",6] = sig_diffs["F4_ɘ",4]
sig_diffs["F4_ɘ",3:4] = NA
sig_diffs["F4_oː",5] = sig_diffs["F4_oː",3]
sig_diffs["F4_oː",6] = sig_diffs["F4_oː",4]
sig_diffs["F4_oː",3:4] = NA
# determine intervals where all smooths are different
# to disregard NAs, use na.rm=TRUE
sig_diffs[length(all_sig_diff_intervals)+1,1] = max(sig_diffs[,1])
sig_diffs[length(all_sig_diff_intervals)+1,2] = min(sig_diffs[,2])
sig_diffs[length(all_sig_diff_intervals)+1,3] = max(sig_diffs[,3])
sig_diffs[length(all_sig_diff_intervals)+1,4] = min(sig_diffs[,4])
sig_diffs[length(all_sig_diff_intervals)+1,5] = max(sig_diffs[,5])
sig_diffs[length(all_sig_diff_intervals)+1,6] = min(sig_diffs[,6])
# -> There are no intervals where all smooths are different!!!
# update row names
row.names(sig_diffs) = c(names, "overall")
# write variable to .csv file
write.csv(sig_diffs, file = "NZE.gam.AR.Mod2_intervals_of_significant_differences.csv")
rm(list=ls(pattern="^int_sig_diff"))
rm(list, all_sig_diff_intervals, sig_diffs, names, max_sig_diff_intervals)

# load final model for H2 Tongan
Tongan.gam.AR.Mod2 = readRDS("updated_models/Tongan.gam.AR.Mod2.rds")

3 Plot final model outputs: Tongan.gam.AR.Mod2

3.1 Vowel “a”

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="a", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): a. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="a", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): a. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="a", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): a. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="a", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): a. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="a", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): a. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

3.2 Vowel “e”

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="e", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="e", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="e", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="e", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="e", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

3.3 Vowel “i”

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="i", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): i. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="i", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): i. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="i", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): i. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="i", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): i. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="i", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): i. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

3.4 Vowel “u”

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="u", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="u", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="u", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="u", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="u", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

3.5 Vowel “o”

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb2", var2="o", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F3", var2="o", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="Bb3", var2="o", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="D4", var2="o", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

plotly_smooths_w_sig_diff(model="Tongan.gam.AR.Mod2", condition="tokenPooled.ord", 
                var1="F4", var2="o", values="theta_uncut_z", language="Tongan")

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

NULL

# combine int_sig_diff... from workspace
all_sig_diff_intervals = (list=ls(pattern="^int_sig_diff"))
max_sig_diff_intervals = 0
for (i in 1:length(all_sig_diff_intervals)){
  if (length(get(all_sig_diff_intervals[i]))>max_sig_diff_intervals){
    max_sig_diff_intervals = length(get(all_sig_diff_intervals[i]))
  }
}
# set up data.frame to store information
sig_diffs = array(NA, c(length(all_sig_diff_intervals), max_sig_diff_intervals))
sig_diffs = data.frame(sig_diffs)
if (max_sig_diff_intervals==8){
  colnames(sig_diffs) = c("low_int1","high_int1","low_int2","high_int2",
                          "low_int3","high_int3","low_int4","high_int4")
}else if (max_sig_diff_intervals==6){
  colnames(sig_diffs) = c("low_int1","high_int1","low_int2","high_int2","low_int3","high_int3")
}else if (max_sig_diff_intervals==4){
  colnames(sig_diffs) = c("low_int1","high_int1","low_int2","high_int2")
}else{
  colnames(sig_diffs) = c("low_int1","high_int1")
}
# create empty list for row names
names = rep(list("NA"), length(all_sig_diff_intervals))
# loop through variable and write information to data.frame
for (i in 1:length(all_sig_diff_intervals)){
  names[i] = paste0(unlist(strsplit(all_sig_diff_intervals[i], "_"))[4], "_",
                    unlist(strsplit(all_sig_diff_intervals[i], "_"))[5])
  sig_diffs[i, 1] = get(all_sig_diff_intervals[i])[1]
  sig_diffs[i, 2] = get(all_sig_diff_intervals[i])[2]
  if (length(get(all_sig_diff_intervals[i]))>=4){
    sig_diffs[i, 3] = get(all_sig_diff_intervals[i])[3]
    sig_diffs[i, 4] = get(all_sig_diff_intervals[i])[4]
  }
  if (length(get(all_sig_diff_intervals[i]))>=6){
    sig_diffs[i, 5] = get(all_sig_diff_intervals[i])[5]
    sig_diffs[i, 6] = get(all_sig_diff_intervals[i])[6]
  }
  if (length(get(all_sig_diff_intervals[i]))==8){
    sig_diffs[i, 7] = get(all_sig_diff_intervals[i])[7]
    sig_diffs[i, 8] = get(all_sig_diff_intervals[i])[8]
  }
}
row.names(sig_diffs) = names
rm(i)
# inspect sig_diffs data.frame and move entries for conditions with only 
# one significantly different interval to other edge, if applicable
sig_diffs["Bb2_e",5] = sig_diffs["Bb2_e",3]
sig_diffs["Bb2_e",6] = sig_diffs["Bb2_e",4]
sig_diffs["Bb2_e",3:4] = NA
sig_diffs["Bb2_e",3] = sig_diffs["Bb2_e",1]
sig_diffs["Bb2_e",4] = sig_diffs["Bb2_e",2]
sig_diffs["Bb2_e",1:2] = NA
sig_diffs["Bb2_i",7] = sig_diffs["Bb2_i",5]
sig_diffs["Bb2_i",8] = sig_diffs["Bb2_i",6]
sig_diffs["Bb2_i",5:6] = NA
sig_diffs["Bb2_i",5] = sig_diffs["Bb2_i",3]
sig_diffs["Bb2_i",6] = sig_diffs["Bb2_i",4]
sig_diffs["Bb2_i",3:4] = NA
sig_diffs["Bb2_i",3] = sig_diffs["Bb2_i",1]
sig_diffs["Bb2_i",4] = sig_diffs["Bb2_i",2]
sig_diffs["Bb2_i",1:2] = NA
sig_diffs["Bb2_o",7] = sig_diffs["Bb2_o",3]
sig_diffs["Bb2_o",8] = sig_diffs["Bb2_o",4]
sig_diffs["Bb2_o",3:4] = NA
sig_diffs["Bb2_u",7] = sig_diffs["Bb2_u",1]
sig_diffs["Bb2_u",8] = sig_diffs["Bb2_u",2]
sig_diffs["Bb2_u",1:2] = NA
sig_diffs["Bb3_e",5] = sig_diffs["Bb3_e",3]
sig_diffs["Bb3_e",6] = sig_diffs["Bb3_e",4]
sig_diffs["Bb3_e",3:4] = NA
sig_diffs["Bb3_e",3] = sig_diffs["Bb3_e",1]
sig_diffs["Bb3_e",4] = sig_diffs["Bb3_e",2]
sig_diffs["Bb3_e",1:2] = NA
sig_diffs["Bb3_i",5] = sig_diffs["Bb3_i",3]
sig_diffs["Bb3_i",6] = sig_diffs["Bb3_i",4]
sig_diffs["Bb3_i",3:4] = NA
sig_diffs["Bb3_i",3] = sig_diffs["Bb3_i",1]
sig_diffs["Bb3_i",4] = sig_diffs["Bb3_i",2]
sig_diffs["Bb3_i",1:2] = NA
sig_diffs["Bb3_o",7] = sig_diffs["Bb3_o",3]
sig_diffs["Bb3_o",8] = sig_diffs["Bb3_o",4]
sig_diffs["Bb3_o",3:4] = NA
sig_diffs["Bb3_u",7] = sig_diffs["Bb3_u",1]
sig_diffs["Bb3_u",8] = sig_diffs["Bb3_u",2]
sig_diffs["Bb3_u",1:2] = NA
sig_diffs["D4_e",3] = sig_diffs["D4_e",1]
sig_diffs["D4_e",4] = sig_diffs["D4_e",2]
sig_diffs["D4_e",1:2] = NA
sig_diffs["D4_i",5] = sig_diffs["D4_i",3]
sig_diffs["D4_i",6] = sig_diffs["D4_i",4]
sig_diffs["D4_i",3:4] = NA
sig_diffs["D4_i",3] = sig_diffs["D4_i",1]
sig_diffs["D4_i",4] = sig_diffs["D4_i",2]
sig_diffs["D4_i",1:2] = NA
sig_diffs["D4_o",7] = sig_diffs["D4_o",1]
sig_diffs["D4_o",8] = sig_diffs["D4_o",2]
sig_diffs["D4_o",1:2] = NA
sig_diffs["D4_u",7] = sig_diffs["D4_u",1]
sig_diffs["D4_u",8] = sig_diffs["D4_u",2]
sig_diffs["D4_u",1:2] = NA
sig_diffs["F3_e",5] = sig_diffs["F3_e",3]
sig_diffs["F3_e",6] = sig_diffs["F3_e",4]
sig_diffs["F3_e",3:4] = NA
sig_diffs["F3_e",3] = sig_diffs["F3_e",1]
sig_diffs["F3_e",4] = sig_diffs["F3_e",2]
sig_diffs["F3_e",1:2] = NA
sig_diffs["F3_o",7] = sig_diffs["F3_o",1]
sig_diffs["F3_o",8] = sig_diffs["F3_o",2]
sig_diffs["F3_o",1:2] = NA
sig_diffs["F3_u",7] = sig_diffs["F3_u",1]
sig_diffs["F3_u",8] = sig_diffs["F3_u",2]
sig_diffs["F3_u",1:2] = NA
sig_diffs["F4_i",5] = sig_diffs["F4_i",3]
sig_diffs["F4_i",6] = sig_diffs["F4_i",4]
sig_diffs["F4_i",3:4] = NA
sig_diffs["F4_i",3] = sig_diffs["F4_i",1]
sig_diffs["F4_i",4] = sig_diffs["F4_i",2]
sig_diffs["F4_i",1:2] = NA
sig_diffs["F4_o",7] = sig_diffs["F4_o",3]
sig_diffs["F4_o",8] = sig_diffs["F4_o",4]
sig_diffs["F4_o",3:4] = NA
sig_diffs["F4_u",7] = sig_diffs["F4_u",1]
sig_diffs["F4_u",8] = sig_diffs["F4_u",2]
sig_diffs["F4_u",1:2] = NA
# determine intervals where all smooths are different
# to disregard NAs, use na.rm=TRUE
sig_diffs[length(all_sig_diff_intervals)+1,1] = max(sig_diffs[,1])
sig_diffs[length(all_sig_diff_intervals)+1,2] = min(sig_diffs[,2])
sig_diffs[length(all_sig_diff_intervals)+1,3] = max(sig_diffs[,3])
sig_diffs[length(all_sig_diff_intervals)+1,4] = min(sig_diffs[,4])
sig_diffs[length(all_sig_diff_intervals)+1,5] = max(sig_diffs[,5])
sig_diffs[length(all_sig_diff_intervals)+1,6] = min(sig_diffs[,6])
# -> There are no intervals where all smooths are different!!!
# update row names
row.names(sig_diffs) = c(names, "overall")
# write variable to .csv file
write.csv(sig_diffs, file = "Tongan.gam.AR.Mod2_intervals_of_significant_differences.csv")
rm(list=ls(pattern="^int_sig_diff"))
rm(list, all_sig_diff_intervals, sig_diffs, names, max_sig_diff_intervals)

4 Plot all vowels together

4.1 NZE

# define colors from PhD thesis
RED0 = (rgb(213,13,11, 255, maxColorValue=255))
BROWN0 = (rgb(123,73,55,255, maxColorValue=255))
# BLUE0 = (rgb(0,98,172,255, maxColorValue=255))
PURPLE0 = (rgb(143,72,183,255, maxColorValue=255))
GRAY0 = (rgb(108,108,108,255, maxColorValue=255))
GREEN0 = (rgb(0,151,55,255, maxColorValue=255))
ORANGE0 = (rgb(255,123,0,255, maxColorValue=255))
PINK0 = (rgb(224,130,180,255, maxColorValue=255))
TEAL0 = (rgb(0,175,195,255, maxColorValue=255))
GOLD0 = (rgb(172,181,0,255, maxColorValue=255))
# GOLD3 = (rgb(224,223,157,255, maxColorValue=255))
# BLUE3 = (rgb(187,210,237,255, maxColorValue=255))
# old color vector col=c("black", "black", GOLD0, GREEN0, ORANGE0, RED0, GRAY0,BROWN0, BLUE0, GOLD0, PURPLE0, PINK0, TEAL0)
light_blue=rgb(0,117,220,255,maxColorValue=255) #col2
black=rgb(25,25,25,255,maxColorValue=255) #col5
pink=rgb(194,0,136,255,maxColorValue=255) #col13
dark_blue=rgb(0,51,128,255,maxColorValue=255) #col14
dark_red=rgb(153,0,0,255,maxColorValue=255)
# discarded
# bright_torquoise=rgb(94,241,242,255,maxColorValue=255) #col19
# light_purple=rgb(116,10,255,255,maxColorValue=255)
# correct order
colors = c(ORANGE0, dark_blue, GREEN0, light_blue, PINK0, GOLD0, BROWN0, TEAL0, GRAY0, dark_red,
           RED0, PURPLE0, pink)
# colorblind safe
# colors = brewer.pal(11,"RdYlBu")
# run plot_smooth to grab values for fit, upper & lower bounds
p1=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="iː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): iː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p2=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="e"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p3=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ʉː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʉː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p4=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɛ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɛ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p5=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɵː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɵː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p6=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɘ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɘ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p7=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p8=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ʊ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʊ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p9=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə#"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p10=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɐ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p11=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɐː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p12=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɒ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p13=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="oː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): oː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

smooth_names=c("FLEECE /iː/","DRESS /e/","GOOSE /ʉː/","TRAP /ɛ/","NURSE /ɵː/","KIT /ɘ/",
               "non-final schwa /ə/","FOOT /ʊ/","final schwa /ə#/","STRUT /ɐ/","START /ɐː/",
               "LOT /ɒ/","THOUGHT /oː/")
# set Rho max to the max of the fit + half the difference between max of the fit and the upper limit
max_ul = max(p1$fv$ul, p2$fv$ul, p3$fv$ul, p4$fv$ul, p5$fv$ul, p6$fv$ul, p7$fv$ul, p8$fv$ul, p9$fv$ul, p10$fv$ul, p11$fv$ul, p12$fv$ul, p13$fv$ul)
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit, p11$fv$fit, p12$fv$fit, p13$fv$fit)
maximum=max_fit+((max_ul-max_fit)/2)
rm(max_ul, max_fit)
# plot in polar coordinates with confidence bounds
plot1=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], dash="dash", width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color=colors[1], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color=colors[1], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5),
            name=smooth_names[2]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], width=2.5),
            name=smooth_names[3]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ul, line=list(color=colors[3], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ll, line=list(color=colors[3], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], dash="dash", width=2.5), name=smooth_names[4]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ul, line=list(color=colors[4], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ll, line=list(color=colors[4], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5),
            name=smooth_names[5]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ul, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ll, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], dash="dash", width=2.5), name=smooth_names[6]) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$ul, line=list(color=colors[6], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$ll, line=list(color=colors[6], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], width=2.5),
            name=smooth_names[7]) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$ul, line=list(color=colors[7], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$ll, line=list(color=colors[7], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dash", width=2.5), name=smooth_names[8]) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$ul, line=list(color=colors[8], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$ll, line=list(color=colors[8], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], width=2.5),
            name=smooth_names[9]) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$ul, line=list(color=colors[9], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$ll, line=list(color=colors[9], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5),
            name=smooth_names[10]) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$ul, line=list(color=colors[10], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$ll, line=list(color=colors[10], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p11$fv$theta_uncut_z*180/pi, r=p11$fv$fit, line=list(color=colors[11], width=2.5),
            name=smooth_names[11]) %>%
  add_trace(theta=p11$fv$theta_uncut_z*180/pi, r=p11$fv$ul, line=list(color=colors[11], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p11$fv$theta_uncut_z*180/pi, r=p11$fv$ll, line=list(color=colors[11], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p12$fv$theta_uncut_z*180/pi, r=p12$fv$fit, line=list(color=colors[12], dash="dash", width=2.5), name=smooth_names[12]) %>%
  add_trace(theta=p12$fv$theta_uncut_z*180/pi, r=p12$fv$ul, line=list(color=colors[12], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p12$fv$theta_uncut_z*180/pi, r=p12$fv$ll, line=list(color=colors[12], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p13$fv$theta_uncut_z*180/pi, r=p13$fv$fit, line=list(color=colors[13], width=2.5),
            name=smooth_names[13]) %>%
  add_trace(theta=p13$fv$theta_uncut_z*180/pi, r=p13$fv$ul, line=list(color=colors[13], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p13$fv$theta_uncut_z*180/pi, r=p13$fv$ll, line=list(color=colors[13], dash="dot", width=0.5), showlegend=FALSE) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="All vowels produced by NZE speakers")
plot1

# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit, p11$fv$fit, p12$fv$fit, p13$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates with confidence bounds
plot2=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], dash="dash", width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5),
            name=smooth_names[2]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], width=2.5),
            name=smooth_names[3]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], dash="dash", width=2.5), name=smooth_names[4]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5),
            name=smooth_names[5]) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], dash="dash", width=2.5), name=smooth_names[6]) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], width=2.5),
            name=smooth_names[7]) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dash", width=2.5), name=smooth_names[8]) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], width=2.5),
            name=smooth_names[9]) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5),
            name=smooth_names[10]) %>%
  add_trace(theta=p11$fv$theta_uncut_z*180/pi, r=p11$fv$fit, line=list(color=colors[11], width=2.5),
            name=smooth_names[11]) %>%
  add_trace(theta=p12$fv$theta_uncut_z*180/pi, r=p12$fv$fit, line=list(color=colors[12], dash="dash", width=2.5), name=smooth_names[12]) %>%
  add_trace(theta=p13$fv$theta_uncut_z*180/pi, r=p13$fv$fit, line=list(color=colors[13], width=2.5),
            name=smooth_names[13]) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="All vowels produced by NZE speakers")
plot2

rm(p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12,p13)

4.2 NZE -> add notes

# correct order
colors = c(ORANGE0, dark_blue, GREEN0, light_blue, PINK0, GOLD0, BROWN0, TEAL0, GRAY0, dark_red,
           RED0, PURPLE0, pink, black, black, black, black, black)
# colorblind safe
# colors = brewer.pal(11,"RdYlBu")
# run plot_smooth to grab values for fit, upper & lower bounds
p1=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="iː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): iː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p2=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="e"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p3=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ʉː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʉː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p4=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɛ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɛ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p5=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɵː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɵː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p6=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɘ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɘ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p7=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p8=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ʊ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ʊ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p9=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə#"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p10=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɐ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p11=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɐː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɐː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p12=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɒ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p13=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="oː"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): oː. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

# add notes
p14=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p15=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="D4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p16=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p17=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p18=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb2"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

# smooth_names=c("FLEECE /iː/","DRESS /e/","GOOSE /ʉː/","TRAP /ɛ/","NURSE /ɵː/","KIT /ɘ/",
#                "non-final schwa /ə/","FOOT /ʊ/","final schwa /ə#/","STRUT /ɐ/","START /ɐː/",
#                "LOT /ɒ/","THOUGHT /oː/","Bb2","F3","Bb3","D4","F4")
# updated order
smooth_names=c("FLEECE /iː/","DRESS /e/","GOOSE /ʉː/","TRAP /ɛ/","NURSE /ɵː/","KIT /ɘ/",
               "non-final schwa /ə/","FOOT /ʊ/","final schwa /ə#/","STRUT /ɐ/","START /ɐː/",
               "LOT /ɒ/","THOUGHT /oː/","F4","D4","Bb3","F3","Bb2")
# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit, p11$fv$fit, p12$fv$fit, p13$fv$fit, p14$fv$fit, p15$fv$fit, p16$fv$fit, p17$fv$fit, p18$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates with confidence bounds
p=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], dash="dash", width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5),
            name=smooth_names[2]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], width=2.5),
            name=smooth_names[3]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], dash="dash", width=2.5), name=smooth_names[4]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5),
            name=smooth_names[5]) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], dash="dash", width=2.5), name=smooth_names[6]) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], width=2.5),
            name=smooth_names[7]) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dash", width=2.5), name=smooth_names[8]) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], width=2.5),
            name=smooth_names[9]) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5),
            name=smooth_names[10]) %>%
  add_trace(theta=p11$fv$theta_uncut_z*180/pi, r=p11$fv$fit, line=list(color=colors[11], width=2.5),
            name=smooth_names[11]) %>%
  add_trace(theta=p12$fv$theta_uncut_z*180/pi, r=p12$fv$fit, line=list(color=colors[12], dash="dash", width=2.5), name=smooth_names[12]) %>%
  add_trace(theta=p13$fv$theta_uncut_z*180/pi, r=p13$fv$fit, line=list(color=colors[13], width=2.5),
            name=smooth_names[13]) %>%
  # updated order
  add_trace(theta=p14$fv$theta_uncut_z*180/pi, r=p14$fv$fit, line=list(color=colors[14], width=1),
            name=smooth_names[14]) %>%
  add_trace(theta=p15$fv$theta_uncut_z*180/pi, r=p15$fv$fit, line=list(color=colors[15], dash="dashdot", width=2.5), name=smooth_names[15]) %>%
  add_trace(theta=p16$fv$theta_uncut_z*180/pi, r=p16$fv$fit, line=list(color=colors[16], dash="dot", width=2.5), name=smooth_names[16]) %>%
  add_trace(theta=p17$fv$theta_uncut_z*180/pi, r=p17$fv$fit, line=list(color=colors[17], dash="dash", width=2.5), name=smooth_names[17]) %>%
  add_trace(theta=p18$fv$theta_uncut_z*180/pi, r=p18$fv$fit, line=list(color=colors[18], width=2.5),
            name=smooth_names[18]) %>%
  # add_trace(theta=p14$fv$theta_uncut_z*180/pi, r=p14$fv$fit, line=list(color=colors[14], width=2.5),
  #           name=smooth_names[14]) %>%
  # add_trace(theta=p15$fv$theta_uncut_z*180/pi, r=p15$fv$fit, line=list(color=colors[15], dash="dash", width=2.5),
  #           name=smooth_names[15]) %>%
  # add_trace(theta=p16$fv$theta_uncut_z*180/pi, r=p16$fv$fit, line=list(color=colors[16], dash="dot", width=2.5),
  #           name=smooth_names[16]) %>%
  # add_trace(theta=p17$fv$theta_uncut_z*180/pi, r=p17$fv$fit, line=list(color=colors[17], dash="dashdot", width=2.5),
  #           name=smooth_names[17]) %>%
  # add_trace(theta=p18$fv$theta_uncut_z*180/pi, r=p18$fv$fit, line=list(color=colors[18], width=1),
  #           name=smooth_names[18]) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="All vowels produced by NZE speakers")
p

rm(p1,p2,p3,p4,p5,p6,p7,p8,p9,p10,p11,p12,p13,p14,p15,p16,p17,p18)

4.3 Tongan

# use colors from PhD thesis (loaded above)
colors = c(ORANGE0, dark_blue, RED0, pink, GREEN0)
# colorblind safe
# colors = brewer.pal(11,"RdYlBu")[c(1,2,4,9,11)]
# run plot_smooth to grab values for fit, upper & lower bounds
p1=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="i"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): i. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p2=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="e"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p3=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="a"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): a. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p4=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="o"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p5=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="u"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

smooth_names=c("/i/","/e/","/a/","/o/","/u/")
# set Rho max to the max of the fit + half the difference between max of the fit and the upper limit
max_ul = max(p1$fv$ul, p2$fv$ul, p3$fv$ul, p4$fv$ul, p5$fv$ul)
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit)
maximum=max_fit+((max_ul-max_fit)/2)
rm(max_ul, max_fit)
# plot in polar coordinates with confidence bounds
plot1=plot_ly(type='scatterpolar', mode='lines') %>% 
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5),
            name=smooth_names[1]) %>% 
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>% 
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>% 
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), 
            name=smooth_names[2]) %>% 
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>% 
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], width=2.5), 
            name=smooth_names[3]) %>% 
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ul, line=list(color=colors[3], dash="dot", width=0.5), showlegend=FALSE) %>% 
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ll, line=list(color=colors[3], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5), 
            name=smooth_names[4]) %>% 
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ul, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>% 
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ll, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5), 
            name=smooth_names[5]) %>% 
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ul, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>% 
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ll, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
         title="All vowels produced by Tongan speakers")
plot1

# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates with confidence bounds
plot2=plot_ly(type='scatterpolar', mode='lines') %>% 
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5),
            name=smooth_names[1]) %>% 
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), 
            name=smooth_names[2]) %>% 
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], width=2.5), 
            name=smooth_names[3]) %>% 
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5), 
            name=smooth_names[4]) %>% 
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5), 
            name=smooth_names[5]) %>% 
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
         title="All vowels produced by Tongan speakers")
plot2

rm(p1,p2,p3,p4,p5)

4.4 Tongan -> add notes

# use colors from PhD thesis (loaded above)
colors = c(ORANGE0, dark_blue, RED0, pink, GREEN0, black, black, black, black, black)
# colorblind safe
# colors = brewer.pal(11,"RdYlBu")[c(1,2,4,9,11)]
# run plot_smooth to grab values for fit, upper & lower bounds
p1=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="i"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): i. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p2=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="e"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): e. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p3=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="a"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): a. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p4=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="o"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p5=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="u"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

# add notes
p6=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p7=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="D4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p8=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p9=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p10=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb2"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

smooth_names=c("/i/","/e/","/a/","/o/","/u/","F4","D4","Bb3","F3","Bb2")
# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates without confidence bounds
plot2=plot_ly(type='scatterpolar', mode='lines') %>% 
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5),
            name=smooth_names[1]) %>% 
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), 
            name=smooth_names[2]) %>% 
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], width=2.5), 
            name=smooth_names[3]) %>% 
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5), 
            name=smooth_names[4]) %>% 
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5), 
            name=smooth_names[5]) %>%
  # updated order
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], width=1), 
            name=smooth_names[6]) %>% 
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], dash="dashdot", width=2.5), name=smooth_names[7]) %>% 
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dot", width=2.5), name=smooth_names[8]) %>% 
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], dash="dash", width=2.5), name=smooth_names[9]) %>% 
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5), 
            name=smooth_names[10]) %>% 
  # add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], width=2.5), 
  #           name=smooth_names[6]) %>% 
  # add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], dash="dash", width=2.5), name=smooth_names[7]) %>% 
  # add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dot", width=2.5), name=smooth_names[8]) %>% 
  # add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], dash="dashdot", width=2.5), 
  #           name=smooth_names[9]) %>% 
  # add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=1), 
  #           name=smooth_names[10]) %>% 
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)), 
         title="All vowels produced by Tongan speakers")
plot2

rm(p1,p2,p3,p4,p5,p6,p7,p8,p9,p10)

4.5 plot vowels closest to playing contours from both languages

colors = c(BROWN0, GRAY0, PURPLE0, pink, GREEN0)
# run plot_smooth to grab values for fit, upper & lower bounds
p1=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p2=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə#"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p3=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɒ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p4=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="o"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p5=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="u"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

smooth_names=c("non-final schwa /ə/ NZE","final schwa /ə#/ NZE","LOT /ɒ/ NZE","/o/ Tongan", "/u/ Tongan")
# set Rho max to the max of the fit + half the difference between max of the fit and the upper limit
max_ul = max(p1$fv$ul, p2$fv$ul, p3$fv$ul, p4$fv$ul, p5$fv$ul)
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit)
maximum=max_fit+((max_ul-max_fit)/2)
rm(max_ul, max_fit)
# plot in polar coordinates with confidence bounds
plot1=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), name=smooth_names[2]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], dash="dash", width=2.5), name=smooth_names[3]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ul, line=list(color=colors[3], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ll, line=list(color=colors[3], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5),
            name=smooth_names[4]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ul, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ll, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5),
            name=smooth_names[5]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ul, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ll, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="Tongan & NZE vowels closest to playing position")
plot1

# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates with confidence bounds
plot2=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), name=smooth_names[2]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], width=2.5, dash="dash"), name=smooth_names[3]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5), name=smooth_names[3]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5), name=smooth_names[5]) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="Tongan & NZE vowels closest to playing position")
plot2

rm(p1,p2,p3)

4.6 plot vowels closest to playing contours from both languages -> with NZE notes!

colors = c(BROWN0, GRAY0, PURPLE0, pink, GREEN0, black, black, black, black, black)
# run plot_smooth to grab values for fit, upper & lower bounds
p1=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p2=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə#"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p3=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɒ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p4=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="o"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p5=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="u"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

# NZE notes
p6=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p7=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="D4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p8=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p9=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p10=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb2"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

smooth_names=c("non-final schwa /ə/ NZE","final schwa /ə#/ NZE","LOT /ɒ/ NZE","/o/ Tongan","/u/ Tongan","F4 NZE","D4 NZE","Bb3 NZE","F3 NZE","Bb2 NZE")
# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates with confidence bounds
plot1=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), name=smooth_names[2]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], dash="dash", width=2.5), name=smooth_names[3]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ul, line=list(color=colors[3], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ll, line=list(color=colors[3], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5),
            name=smooth_names[4]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ul, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ll, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5),
            name=smooth_names[5]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ul, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ll, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], width=1),
            name=smooth_names[6]) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$ul, line=list(color=colors[6], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$ll, line=list(color=colors[6], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], dash="dashdot", width=2.5), name=smooth_names[7]) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$ul, line=list(color=colors[7], dash="dashdot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$ll, line=list(color=colors[7], dash="dashdot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dot", width=2.5), name=smooth_names[8]) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$ul, line=list(color=colors[8], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$ll, line=list(color=colors[8], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], dash="dash", width=2.5), name=smooth_names[9]) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$ul, line=list(color=colors[9], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$ll, line=list(color=colors[9], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5),
            name=smooth_names[10]) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$ul, line=list(color=colors[10], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$ll, line=list(color=colors[10], dash="dot", width=0.5), showlegend=FALSE) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="Tongan & NZE vowels closest to playing position with NZE notes")
plot1

# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates without confidence bounds
plot2=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), name=smooth_names[2]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], dash="dash", width=2.5), name=smooth_names[3]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5), name=smooth_names[4]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5), name=smooth_names[5]) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], width=1), name=smooth_names[6]) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], dash="dashdot", width=2.5), name=smooth_names[7]) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dot", width=2.5), name=smooth_names[8]) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], dash="dash", width=2.5), name=smooth_names[9]) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5),
            name=smooth_names[10]) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="Tongan & NZE vowels closest to playing position with NZE notes")
plot2

rm(p1,p2,p3,p4,p5,p6,p7,p8,p9,p10)

4.7 plot vowels closest to playing contours from both languages -> with Tongan notes!

colors = c(BROWN0, GRAY0, PURPLE0, pink, GREEN0, black, black, black, black, black)
# run plot_smooth to grab values for fit, upper & lower bounds
p1=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p2=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ə#"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ə#. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p3=plot_smooth(x=NZE.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="ɒ"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): ɒ. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.627597 to -0.617214. 
    * subVowelInt : factor; set to the value(s): S3.ə. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): coronals.ə. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p4=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="o"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): o. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p5=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="u"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): u. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

# Tongan notes
p6=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p7=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="D4"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): D4. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p8=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p9=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="F3"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): F3. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

p10=plot_smooth(x=Tongan.gam.AR.Mod2, view="theta_uncut_z", cond=list(tokenPooled.ord="Bb2"), rm.ranef=TRUE)

Summary:
    * tokenPooled.ord : factor; set to the value(s): Bb2. 
    * theta_uncut_z : numeric predictor; with 30 values ranging from -2.648777 to -0.708619. 
    * subVowelInt : factor; set to the value(s): S16.F3. (Might be canceled as random effect, check below.) 
    * precSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * follSoundVowelInt : factor; set to the value(s): mezzoforte.F3. (Might be canceled as random effect, check below.) 
    * NOTE : The following random effects columns are canceled: s(theta_uncut_z,subVowelInt),s(theta_uncut_z,precSoundVowelInt),s(theta_uncut_z,follSoundVowelInt)
 

smooth_names=c("non-final schwa /ə/ NZE","final schwa /ə#/ NZE","LOT /ɒ/ NZE","/o/ Tongan","/u/ Tongan","F4 Tongan","D4 Tongan","Bb3 Tongan","F3 Tongan","Bb2 Tongan")
# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates with confidence bounds
plot1=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ul, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$ll, line=list(color=colors[1], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), name=smooth_names[2]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ul, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$ll, line=list(color=colors[2], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], dash="dash", width=2.5), name=smooth_names[3]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ul, line=list(color=colors[3], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$ll, line=list(color=colors[3], dash="dash", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5),
            name=smooth_names[4]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ul, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$ll, line=list(color=colors[4], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5),
            name=smooth_names[5]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ul, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$ll, line=list(color=colors[5], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], width=1),
            name=smooth_names[6]) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$ul, line=list(color=colors[6], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$ll, line=list(color=colors[6], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], dash="dashdot", width=2.5), name=smooth_names[7]) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$ul, line=list(color=colors[7], dash="dashdot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$ll, line=list(color=colors[7], dash="dashdot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dot", width=2.5), name=smooth_names[8]) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$ul, line=list(color=colors[8], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$ll, line=list(color=colors[8], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], dash="dash", width=2.5), name=smooth_names[9]) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$ul, line=list(color=colors[9], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$ll, line=list(color=colors[9], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5),
            name=smooth_names[10]) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$ul, line=list(color=colors[10], dash="dot", width=0.5), showlegend=FALSE) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$ll, line=list(color=colors[10], dash="dot", width=0.5), showlegend=FALSE) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="Tongan & NZE vowels closest to playing position with Tongan notes")
plot1

# set Rho max to the max of the fit + 5
max_fit = max(p1$fv$fit, p2$fv$fit, p3$fv$fit, p4$fv$fit, p5$fv$fit, p6$fv$fit, p7$fv$fit, p8$fv$fit, p9$fv$fit, p10$fv$fit)
maximum=max_fit+5
rm(max_fit)
# plot in polar coordinates without confidence bounds
plot2=plot_ly(type='scatterpolar', mode='lines') %>%
  add_trace(theta=p1$fv$theta_uncut_z*180/pi, r=p1$fv$fit, line=list(color=colors[1], width=2.5), name=smooth_names[1]) %>%
  add_trace(theta=p2$fv$theta_uncut_z*180/pi, r=p2$fv$fit, line=list(color=colors[2], width=2.5), name=smooth_names[2]) %>%
  add_trace(theta=p3$fv$theta_uncut_z*180/pi, r=p3$fv$fit, line=list(color=colors[3], dash="dash", width=2.5), name=smooth_names[3]) %>%
  add_trace(theta=p4$fv$theta_uncut_z*180/pi, r=p4$fv$fit, line=list(color=colors[4], width=2.5), name=smooth_names[4]) %>%
  add_trace(theta=p5$fv$theta_uncut_z*180/pi, r=p5$fv$fit, line=list(color=colors[5], width=2.5), name=smooth_names[5]) %>%
  add_trace(theta=p6$fv$theta_uncut_z*180/pi, r=p6$fv$fit, line=list(color=colors[6], width=1), name=smooth_names[6]) %>%
  add_trace(theta=p7$fv$theta_uncut_z*180/pi, r=p7$fv$fit, line=list(color=colors[7], dash="dashdot", width=2.5), name=smooth_names[7]) %>%
  add_trace(theta=p8$fv$theta_uncut_z*180/pi, r=p8$fv$fit, line=list(color=colors[8], dash="dot", width=2.5), name=smooth_names[8]) %>%
  add_trace(theta=p9$fv$theta_uncut_z*180/pi, r=p9$fv$fit, line=list(color=colors[9], dash="dash", width=2.5), name=smooth_names[9]) %>%
  add_trace(theta=p10$fv$theta_uncut_z*180/pi, r=p10$fv$fit, line=list(color=colors[10], width=2.5),
            name=smooth_names[10]) %>%
  layout(polar=list(sector=c(20,160), radialaxis=list(angle=90, range=c(0,maximum)),
                    angularaxis=list(thetaunit='radians', direction="clockwise", rotation=0)),
         title="Tongan & NZE vowels closest to playing position with Tongan notes")
plot2

rm(p1,p2,p3,p4,p5,p6,p7,p8,p9,p10)