Matched case-control data analyses with missing covariates

Myunghee Cho Paik, Ralph L. Sacco

Research output: Contribution to journalArticle

26 Scopus citations

Abstract

We consider methods for analysing matched case-control data when some covariates (W) are completely observed but other covariates (X) are missing for some subjects. In matched case-control studies, the complete-record analysis discards completely observed subjects if none of their matching cases or controls are completely observed. We investigate an imputation estimate obtained by solving a joint estimating equation for log-odds ratios of disease and parameters in an imputation model. Imputation estimates for coefficients of W are shown to have smaller bias and mean-square error than do estimates from the complete-record analysis.

Original languageEnglish (US)
Pages (from-to)145-156
Number of pages12
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume49
Issue number1
DOIs
StatePublished - Jan 1 2000

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Keywords

  • Matched case-control study
  • Mean imputation
  • Missing covariates

ASJC Scopus subject areas

  • Mathematics(all)
  • Statistics and Probability

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