Growth Curve Analysis Workshop

Overview

These are slides from a one-day virtual Growth Curve Analysis (GCA) workshop organized by the graduate student association at Rutgers University in May 2020. The purpose of the workshop was to provide a hands-on introduction to using GCA to analyze longitudinal or time course data. The workshop was conducted in R (and RStudio) using the following packages:

tidyverse: for data management and graphing.
lme4, lmerTest: for fitting growth curve models.
psy811: example data sets and helper functions.

For pre-processing eye-tracking data, I recommend our gazeR package (Geller et al., in press), which also contains the GCA helper functions (it does not have all of the example data sets for this workshop).

Workshop Slides

Part 1	Introduction (challenges of time course data), GCA basics
Part 2	Modeling nonlinear change
Part 3	Within-subject effects, random effects structures
Part 4	Logistic GCA
Part 5	Quantifying and analyzing individual differences

Exercise solutions