Accounting for missing data in statistical analyses: multiple imputation is not always the answer

A. Hughes, Rachael; Heron, Jon; A C Sterne, Jonathan; Tilling, Kate

doi:10.1093/ije/dyz032

Public

Accounting for missing data in statistical analyses: multiple imputation is not always the answer

Published in International Journal of Epidemiology • Mar 5, 2019

Authors:

Rachael A. Hughes

Jon Heron

Jonathan A C Sterne

Abstract

BACKGROUND: Missing data are unavoidable in epidemiological research, potentially leading to bias and loss of precision. Multiple imputation (MI) is widely advocated as an improvement over complete case analysis (CCA). However, contrary to widespread belief, CCA is preferable to MI in some situation...

Subject

Missing data

Imputation (statistics)

Covariate

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