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.
|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|