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

Author

Listed:
  • Jonathan W. Bartlett

    (London School of Hygiene and Tropical Medicine)

  • Tim P. Morris

    (MRC Clinical Trials Unit at UCL)

Abstract

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 smcfcs 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 smcfcs 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. Copyright 2015 by StataCorp LP.

Suggested Citation

  • Jonathan W. Bartlett & Tim P. Morris, 2015. "Multiple imputation of covariates by substantive-model compatible fully conditional specification," Stata Journal, StataCorp LP, vol. 15(2), pages 437-456, June.
    • Handle: RePEc:tsj:stataj:v:15:y:2015:i:2:p:437-456
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    Citations

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    Cited by:

    1. Lily Clements & Alan C. Kimber & Stefanie Biedermann, 2022. "Multiple Imputation of Composite Covariates in Survival Studies," Stats, MDPI, vol. 5(2), pages 1-13, March.
    2. Liu, Yishuang & Huang, Jinpeng & Xu, Jianxiang & Xiong, Shufei, 2024. "Natural resource dependence and sustainable development policy: Insights from city-level analysis," Resources Policy, Elsevier, vol. 91(C).
    3. Lauren J. Beesley & Jeremy M. G. Taylor, 2021. "A stacked approach for chained equations multiple imputation incorporating the substantive model," Biometrics, The International Biometric Society, vol. 77(4), pages 1342-1354, December.

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