The analysis of binary longitudinal data with time independent covariates

Scott L. Zeger; Kung Yee Liang; Steven G. Self

doi:10.1093/biomet/72.1.31

The analysis of binary longitudinal data with time independent covariates

Scott L. Zeger, Kung Yee Liang, Steven G. Self

Bloomberg School of Public Health

Research output: Contribution to journal › Article › peer-review

81 Scopus citations

Abstract

This paper considers extensions of logistic regression to the case where the binary outcome variable is observed repeatedly for each subject. We propose two working models that lead to consistent estimates of the regression parameters and of their variances under mild assumptions about the time dependence within each subject's data. The efficiency of the proposed estimators is examined. An analysis of stress in mothers with infants is presented to illustrate the proposed method.

Original language	English (US)
Pages (from-to)	31-38
Number of pages	8
Journal	Biometrika
Volume	72
Issue number	1
DOIs	https://doi.org/10.1093/biomet/72.1.31
State	Published - Apr 1 1985

Keywords

Binary longitudinal data
Logistic regression
Markov chain
Maximum likelihood

ASJC Scopus subject areas

Statistics and Probability
General Mathematics
Agricultural and Biological Sciences (miscellaneous)
General Agricultural and Biological Sciences
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1093/biomet/72.1.31

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AB - This paper considers extensions of logistic regression to the case where the binary outcome variable is observed repeatedly for each subject. We propose two working models that lead to consistent estimates of the regression parameters and of their variances under mild assumptions about the time dependence within each subject's data. The efficiency of the proposed estimators is examined. An analysis of stress in mothers with infants is presented to illustrate the proposed method.

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KW - Markov chain

KW - Maximum likelihood

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The analysis of binary longitudinal data with time independent covariates

Abstract

Keywords

ASJC Scopus subject areas

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