Using the plotmachine
The plotmachine computes F1 and F2 means for any number of predictors and then plots those using ggplot.
Download it here. Save as a text file and run it in R.
The plotmachine takes the following input:
plotmachine=function(dataset, vowel, F1, F2, ..., plot_title=" ") Arguments: dataset --- the dataset you're working with. Needs to be created first, e.g. by reading in a spreadsheet with read.csv(). vowel --- the name of the column within this dataset that contains the vowel labels. F1 --- the name of the column within this dataset that contains the F1 measurements. F2 --- the name of the column within this dataset that contains the F2 measurements. ... --- any number of independent variables that you want to plot . title --- the title of your plot, also part of the name of the file your plot will be saved as. Defaults to " ".
For one independent variable, it prints out the means by category, outputs and saves a plot as a png file. For several independent variables, it prints out means and creates plots for all combinations of variables. It returns the dataframe of means.
Thus, for a dataset called texasenglish, this plots the formants by gender for all vowels that are in a column called VOWEL.
plotmachine(texasenglish, VOWEL, F1NORMALIZED, F2NORMALIZED, GENDER, plot_title="Gender differences in Texas English")
It uses the data found in F1NORMALIZED and F2NORMALIZED. Note that none of the input besides the
plot_title should be in quotation marks.
Note that you can feed it as many independent variables as you like. This example will calculate means by gender, ethnicity and agegroup:
plotmachine(texasenglish, VOWEL, F1NORMALIZED, F2NORMALIZED, GENDER, ETHNICITY, AGEGROUP, plot_title="Random vowel chart")
It will create these plots: gender x ethnicity, gender x age group, ethnicity x agegroup.
Note that you need to have the packages vowels, ggplot2 and lme4 installed for this to work.
To do: return dataframe, check for libraries