Using Generalized Estimating Equations for Longitudinal Data Analysis
Open accessAbstract
The generalized estimating equation (GEE) approach of Zeger and Liang facilitates analysis of data collected in longitudinal, nested, or repeated measures designs. GEEs use the generalized linear model to estimate more efficient and unbiased regression parameters relative to ordinary least squares regression in part because they permit specification of a working correlation matrix that accounts for the form of within-subject correlation of responses on dependent variables of many different distributions, including normal, binomial, and Poisson. The author briefly explains the theory behind GEEs and their beneficial statistical properties and limitations and compares GEEs to suboptimal approaches for analyzing longitudinal data through use of two examples. The first demonstration applies GEEs to the analysis of data from a longitudinal lab study with a counted response variable; the second demonstration applies GEEs to analysis of data with a normally distributed response variable from subjects nested within branch offices ofan organization.
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In the unmatched approach, a logistic regression model using generalised estimating equations was fit to the data to account for the possibility of repeated samples from the same participant.
“In the unmatched approach, a logistic regression model using generalised estimating equations was fit to the data to account for the possibility of repeated samples from the same participant,24 assuming an unstructured correlation matrix.”
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- Authors
- Ballinger, G. A.
- Affiliations
- Purdue University West Lafayette (US)
- Corresponding author
- Ballinger, Gary A.
- ORCID
- Ballinger, Gary A.
- Venue
- Organizational Research Methods
- Publisher
- SAGE Publications
- Published
- 2004-04
- Volume
- 7
- Issue
- 2
- Pages
- 127-150
- ISSN
- 1094-4281 (ISSN-L)
- 1552-7425
- OpenAlex
- W2101831741
- Cited by
- 1,567
- References
- 2
- Citations by year
- 2026: 95 · 2025: 98 · 2024: 102 · 2023: 99 · 2022: 154 · 2021: 135 · 2020: 101 · 2019: 88 · 2018: 88 · 2017: 98 · 2016: 71 · 2015: 81 · 2014: 69 · 2013: 53 · 2012: 61
- FWCI
- 12.15
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Organizational Research Methods (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Spatial and Panel Data Analysis
- Life Sciences › Agricultural and Biological Sciences › Ecology, Evolution, Behavior and Systematics › Agriculture, Soil, Plant Science
- Keywords
- generalized estimating equations, longitudinal analysis, repeated measures, working correlation matrix, within-subject correlation, generalized linear models, count data, nested data, Poisson regression, binomial regression
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