tidy
ggplot2
getVOT
This is a tutorial showing how to generate multitaper spectra in R and how to compute spectral moments and DCT coefficients from multitaper spectra.
This is a tutorial about how to use the {marginaleffects} package to extract and plot predictions of interest from a statistical model.
A tutorial on how to normalize vowel formant measurments in R using the tidyverse
An introduction to using this tutorial. The relationship between R and Goldvarb. Token and script files. R vs. R Studio. How to install packages.
Download the (t,d) deletion data and listen to several examples.
How to import your data into R.
Getting a snapshot of your data. Types of data and data structures. Getting the dimensions of your data. Introducting the (t/d) dataset.
Modifying data, including removing rows, re-coding variables, centering continuous variables, dividing continuous variables, changing the order of variables, reversing the order of variables, combining columns, splitting columns, and partitioning data sets.
Modifying data, but using the tidyverse
tidyverse
Getting token counts and proportions. Getting mean, median, standard deviation, and quartiles. Dealing with decimals and exponential notation.
Generating proportions that you can plot using ggplot2.
Doing an analysis using conditional inference trees.
Doing a basic random forest analysis.
Doing a mixed-effects logistic regression analysis suitable for comparing to a Goldvarb analysis. Part 1: The Setup
Doing a mixed-effects logistic regression analysis suitable for comparing to a Goldvarb analysis. Part 2: Sum Contrast Coding
Doing a mixed-effects logistic regression analysis suitable for comparing to a Goldvarb analysis. Part 3: Correlations, Interactions, & Collinearity
Doing a mixed-effects logistic regression analysis suitable for comparing to a Goldvarb analysis. Part 4: Treatment Contrast Coding
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