The analysis of binary longitudinal data with time independent covariates

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

Research output: Contribution to journalArticle

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 languageEnglish (US)
Pages (from-to)31-38
Number of pages8
JournalBiometrika
Volume72
Issue number1
DOIs
StatePublished - Apr 1 1985

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Keywords

  • Binary longitudinal data
  • Logistic regression
  • Markov chain
  • Maximum likelihood

ASJC Scopus subject areas

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

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