Overview
These are slides from a two-day Eye-Tracking Analysis workshop given at San Diego State University for the SDSU/UCSD Joint Doctoral Program in Language and Communication Sciences in January 2019. The purpose of the workshop was to provide a hands-on introduction to preprocessing eye-tracking data and analyzing those data using growth curve analysis (GCA). The focus was on eye-tracking data, but GCA is broadly applicable to longitudinal or time course data and many of the preprocessing steps apply to other kinds of physiological measures (such as EEG). Day 1 focused on general data "wrangling" and specifically preprocessing eye-tracking data. Day 2 focused on growth curve analysis. The workshop was conducted in R (and RStudio) using the following packages:
- tidyverse packages for reading, managing, and graphing data.
- lme4: for fitting growth curve models.
- gazeR: functions for preprocessing eye-tracking data and example data sets.
- A few additional data sets: Visual Search, Deviant Behavior
Workshop Slides
| Day 1, Part 1 | Data Wrangling |
| Day 1, Part 2 | Pre-Processing Eye-Tracking Data |
| Day 2, Part 1 | GCA Basics |
| Day 2, Part 2 | Non-Linear Change, Within-Subject Effects |
| Day 2, Part 3 | Logistic GCA |
| Day 2, Part 4 | Visualizing Higher-Order Polynomial Terms |
| Day 2, Part 5 | Quantifying and Analyzing Individual Differences Final exercise solution |