Bartlett, JW;
Morris, TP;
(2015)
Multiple imputation of covariates by substantive-model compatible fully conditional specification.
The Stata Journal
, 15
(2)
pp. 437-456.
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Abstract
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 compared to standard FCS imputation using mi impute chained in a simulation study and illustrative analysis of data from a study investigating time to tumour recurrence in breast cancer.
| Type: | Article |
|---|---|
| Title: | Multiple imputation of covariates by substantive-model compatible fully conditional specification |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://www.stata-journal.com/article.html?article=... |
| Language: | English |
| Additional information: | © Copyright 2001–2015 StataCorp LP |
| Keywords: | st0387, smcfcs, multiple imputation, substantive model compatible, congenial, interactions, nonlinearities |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1470042 |
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