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

Epidemiological studies often have missing data, which are commonly handled by multiple imputation (MI). Standard (default) MI procedures use simple linear covariate functions in the imputation model. We examine the bias that may be caused by acceptance of this default option and evaluate methods to identify problematic imputation models, providing practical guidance for researchers.

Source: Journal of Clinical Epidemiology - June 19, 2023 Category: Epidemiology Authors: Elinor Curnow, James R. Carpenter, Jon E. Heron, Rosie P. Cornish, Stefan Rach, Vanessa Didelez, Malte Langeheine, Kate Tilling Tags: Original Article Source Type: research