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SMCFCS: Stata module to perform multiple imputation of covariates by substantive model compatible fully conditional specification

Author

Listed:
  • Jonathan Bartlett

    (AstraZeneca)

  • Tim Morris

    (MRC Clinical Trials Unit at UCL)

Programming Language

Stata

Abstract

smcfcs implements multiple imputation of covariates by substantive model compatible fully conditional specification. This approach modifies the popular fully conditional specification (chained equations) approach to multiple imputation, by ensuring that each covariate is imputed from a model which is compatible with a user specified substantive model. This is particularly useful when the latter contains interactions or non-linear covariate effects, where conventional approaches may lead to biased estimates. At present linear, logistic and Cox proportional hazards substantive models are supported. Competing risks can also be handled, assuming a Cox model for each cause specific hazard function.

Suggested Citation

  • Jonathan Bartlett & Tim Morris, 2015. "SMCFCS: Stata module to perform multiple imputation of covariates by substantive model compatible fully conditional specification," Statistical Software Components S457968, Boston College Department of Economics, revised 16 Feb 2019.
    • Handle: RePEc:boc:bocode:s457968
    Note: This module should be installed from within Stata by typing "ssc install smcfcs". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/s/smcfcs.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/s/smcfcs.sthlp
    File Function: help file
    Download Restriction: no
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