Imputation of missing covariate in randomized controlled trials with a continuous outcome: Scoping review and new results.

ABSTRACT: In this article, we first review the literature on dealing with missing values on a covariate in randomized studies and summarize what has been done and what is lacking to date. We then investigate the situation with a continuous outcome and a missing binary covariate in more details through simulations, comparing the performance of multiple imputation (MI) with various simple alternative methods. This is finally extended to the case of time-to-event outcome. The simulations consider five different missingness scenarios: missing completely at random (MCAR), at random (MAR) with missingness depending only on the treatment, and missing not at random (MNAR) with missingness depending on the covariate itself (MNAR1), missingness depending on both the treatment and covariate (MNAR2), and missin

SUBMITTER: Kayembe MT 

PROVIDER: S-EPMC7687108 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature