tidy

ggplot2

getVOT

An introduction to using this tutorial. The relationship between R and Goldvarb. Token and script files. R vs. R Studio. How to install packages.

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

A tutorial on how to normalize vowel formant measurments in R using the tidyverse

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