Analyzing Cross-Sectionally Clustered Data Using Generalized Estimating Equations

Author(s): Huang, Francis L.
Year: 2022
Title: Analyzing Cross-Sectionally Clustered Data Using Generalized Estimating Equations
Publication title: Journal of Educational and Behavioral Statistics
Volume: 47
Issue: 01
Pages: 101-125
DOI: 10.3102/10769986211017480
URL: https://doi.org/10.3102/10769986211017480
Keywords:
Clustered Data
Education Data
Statistical Methods
Generalized Estimating Equations (Gees)
Population Average Models
Topic:
METHODOLOGY
Data:
HS&B:80
Abstract:

The presence of clustered data is common in the sociobehavioral sciences. One approach that specifically deals with clustered data but has seen little use in education is the generalized estimating equations (GEEs) approach. We provide a background on GEEs, discuss why it is appropriate for the analysis of clustered data, and provide worked examples using both continuous and binary outcomes. Comparisons are made between GEEs, multilevel models, and ordinary least squares results to highlight similarities and differences between the approaches. Detailed walkthroughs are provided using both R and SPSS Version 26.