Analyzing Cross-Sectionally Clustered Data Using Generalized Estimating Equations

Autor/in	Huang, Francis L.
Titel	Analyzing Cross-Sectionally Clustered Data Using Generalized Estimating Equations
Quelle	In: Journal of Educational and Behavioral Statistics, 47 (2022) 1, S.101-125 (25 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/10769986211017480
Schlagwörter	Multivariate Analysis; Computation; Correlation; Error of Measurement; Statistical Analysis + Suchen Sie Ihr Suchwort? Multivariate Analyse; Korrelation; Messfehler; Statistische Analyse
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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01