Lorelogram: A regression approach to exploring dependence in longitudinal categorical responses

Patrick J. Heagerty, Scott L. Zeger

Research output: Contribution to journalArticlepeer-review

Abstract

We propose flexible regression estimators of the marginal pairwise log-odds ratio measure of association for longitudinal categorical responses. The function that we estimate is the log-odds ratio analog of the correlogram; hence we name the function the lorelogram. Measuring the association of categorical responses on the log-odds scale allows ease of interpretation and allows pairwise association to remain unconstrained by the marginal means, a feature not shared by correlations with binary or multinomial responses. Estimation of the function is achieved through the use of standard parametric estimating equations or through an extension of generalized additive models that allows nonparametric estimation of dependence functions for fixed smoothing parameters. We apply the methodology to binary longitudinal data where scientific interest focuses on the dependence structure.

Original languageEnglish (US)
Pages (from-to)150-162
Number of pages13
JournalJournal of the American Statistical Association
Volume93
Issue number441
DOIs
StatePublished - Mar 1 1998

Keywords

  • Correlogram
  • Estimating equation
  • Variogram

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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