Matched case–control data analyses with missing covariates |
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Authors: | M C Paik & R L Sacco |
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Institution: | Columbia University, New York, USA |
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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. |
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Keywords: | Matched case–control study Mean imputation Missing covariates |
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