Multiple imputation of covariates by substantive model compatible fully conditional specification
نویسندگان
چکیده
Multiple imputation (MI) is a practical, principled approach to handling missing data. When used to impute missing values in covariates of regression models, imputation models may be mis-specified if they are not compatible with the substantive model of interest for the outcome. In this article we introduce the smcfcs command, which imputes covariates by substantive model compatible fully conditional specification (SMC–FCS). This modifies the popular FCS or chained equations approach to MI by imputing each covariate compatibly with a user-specified substantive model. The smcfcs command is illustrated through application to data from a study investigating time to tumour recurrence in breast cancer.
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