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

Jonathan Bartlett () and Tim Morris ()
Additional contact information
Jonathan Bartlett: AstraZeneca
Tim Morris: MRC Clinical Trials Unit at UCL

Statistical Software Components from Boston College Department of Economics

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.

Language: Stata
Requires: Stata version 11
Keywords: multiple imputation; covariates; substantive model (search for similar items in EconPapers)
Date: 2015-02-22, Revised 2019-02-16
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.
References: Add references at CitEc
Citations:

Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/s/smcfcs.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/s/smcfcs.sthlp help file (text/plain)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s457968

Ordering information: This software item can be ordered from
http://repec.org/docs/ssc.php

Access Statistics for this software item

More software in Statistical Software Components from Boston College Department of Economics Boston College, 140 Commonwealth Avenue, Chestnut Hill MA 02467 USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().