Regression for Longitudinal Data: A Bridge from Least Squares Regression
- 1 November 1994
- journal article
- research article
- Published by Taylor & Francis in The American Statistician
- Vol. 48 (4) , 299-303
- https://doi.org/10.1080/00031305.1994.10476085
Abstract
Longitudinal studies play a prominent role in biomedical and sociological research. Generalized estimating equations (GEE) provide a regression methodology to analyze the correlated data that often result from a longitudinal study. Many applied researchers are attracted to the informative and valid analyses GEE provides but cannot clear the hurdle of understanding the literature. This article places GEE in more familiar territory by building a link from the well-known least squares regression methodology.Keywords
This publication has 10 references indexed in Scilit:
- A computer program for regression analysis of repeated measures using generalized estimating equationsComputer Methods and Programs in Biomedicine, 1993
- Generalized Linear ModelsPublished by Springer Nature ,1989
- CommentaryStatistics in Medicine, 1988
- Longitudinal Design and Longitudinal AnalysisResearch on Aging, 1986
- Longitudinal Data Analysis for Discrete and Continuous OutcomesPublished by JSTOR ,1986
- Longitudinal data analysis using generalized linear modelsBiometrika, 1986
- Linear Models for the Analysis of Longitudinal StudiesThe American Statistician, 1985
- Iteratively Reweighted Least Squares for Maximum Likelihood Estimation, and Some Robust and Resistant AlternativesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1984
- Seemingly unrelated nonlinear regressionsJournal of Econometrics, 1975