Polychotomous logistic regression methods for matched case-control studies with multiple case or control groups

Kung Yee Liang, Walter F. Stewart

Research output: Contribution to journalArticle

Abstract

Two statistical methods, a polychotomous and pairwise approach, are presented to derive estimates of the relative odds in a matched case-control design when multiple case or control groups are used. Test statistics are derived to determine if the relative odds between groups are different. The polychotomous method is limited to case-control sets, i.e., where data are available on all members of a matched set. in contrast, the pairwise method makes use of data from both complete and incomplete sets. Nonetheless, efficiency calculations show that the polychotomous logistic regression model is more efficient even when 40 per cent of the case-control sets are incomplete. An example using a single dichotomous variable is provided.

Original languageEnglish (US)
Pages (from-to)720-730
Number of pages11
JournalAmerican journal of epidemiology
Volume125
Issue number4
DOIs
StatePublished - Apr 1987

Keywords

  • Epidemiologic methods
  • Regression analysis
  • Retrospective studies
  • Statistics

ASJC Scopus subject areas

  • Epidemiology

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