Multiple imputation of covariates by substantive-model compatible fully conditional specification

作者：Bartlett Jonathan W^*; Morris Tim P

来源：Stata Journal, 2015, 15(2): 437-456.

DOI：10.1177/1536867x1501500206

• st0387
• smcfcs
• multiple imputation
• substantive model compatible
• congenial
• interactions
• nonlinearities

Multiple imputation is a practical, principled approach to handling missing data. When used to impute missing values in covariates of regression models, imputation models may be misspecified if they are not compatible with the substantive model of interest for the outcome. In this article, we introduce the smcf cs command, which imputes covariates by substantive-model compatible fully conditional specification. This modifies the popular fully conditional specification or chained-equations approach to multiple imputation by imputing each covariate compatibly with a user-specified substantive model. We compare the smcf cs command with standard fully conditional specification imputation using mi impute chained in a simulation study and illustrative analysis of data from a study investigating time to tumor recurrence in breast cancer.

• 出版日期2015