Matched case–control data analyses with missing covariates

M. C. Paik and R. L. Sacco

Journal of the Royal Statistical Society Series C, 2000, vol. 49, issue 1, 145-156

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.

Date: 2000
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