eprintid: 1470042 rev_number: 46 eprint_status: archive userid: 608 dir: disk0/01/47/00/42 datestamp: 2015-11-04 16:55:33 lastmod: 2024-07-16 15:32:17 status_changed: 2015-11-04 16:55:33 type: article metadata_visibility: show creators_name: Bartlett, JW creators_name: Morris, TP title: Multiple imputation of covariates by substantive-model compatible fully conditional specification ispublished: pub divisions: UCL divisions: B02 divisions: D65 divisions: J38 keywords: st0387, smcfcs, multiple imputation, substantive model compatible, congenial, interactions, nonlinearities note: © Copyright 2001–2015 StataCorp LP 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. date: 2015-06 date_type: published official_url: http://www.stata-journal.com/article.html?article=st0387 vfaculties: VFPHS oa_status: green full_text_type: other language: eng primo: open primo_central: open_green verified: verified_manual elements_id: 1039917 language_elements: English lyricists_name: Morris, Timothy lyricists_id: TNMOR17 actors_name: Morris, Timothy actors_id: TNMOR17 actors_role: owner full_text_status: public publication: The Stata Journal volume: 15 number: 2 pagerange: 437-456 issn: 1536-867X citation: Bartlett, JW; Morris, TP; (2015) Multiple imputation of covariates by substantive-model compatible fully conditional specification. The Stata Journal , 15 (2) pp. 437-456. Green open access document_url: https://discovery.ucl.ac.uk/id/eprint/1470042/1/morris_smcfcs-final.pdf