Multiple imputation of missing data under missing at random: compatible imputation models are not sufficient to avoid bias if they are mis-specified-Reference-Cited by-同舟云学术

Multiple imputation of missing data under missing at random: compatible imputation models are not sufficient to avoid bias if they are mis-specified

Published:2023-08 Issue: Volume:160 Page:100-109
ISSN:0895-4356
Container-title:Journal of Clinical Epidemiology
language:en
Short-container-title:Journal of Clinical Epidemiology

Author:

Curnow Elinor^ORCID,Carpenter James R.,Heron Jon E.^ORCID,Cornish Rosie P.^ORCID,Rach Stefan^ORCID,Didelez Vanessa^ORCID,Langeheine Malte,Tilling Kate

Funder

Medical Research Council

University of Bristol

Publisher

Elsevier BV

Subject

Epidemiology

Reference22 articles.

1. Missing data: a statistical framework for practice;Carpenter;Biom J,2021

2. Multiple imputation for nonresponse in surveys;Rubin,1987

3. Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: the general location model;Seaman;Stat Methods Med Res,2018

4. Appropriate inclusion of interactions was needed to avoid bias in multiple imputation;Tilling;J Clin Epidemiol,2016

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