The mixed model for repeated measures for cluster randomized trials: a simulation study investigating bias and type I error with missing continuous data.

ABSTRACT:

Background

Cluster randomized trials (CRTs) are a design used to test interventions where individual randomization is not appropriate. The mixed model for repeated measures (MMRM) is a popular choice for individually randomized trials with longitudinal continuous outcomes. This model's appeal is due to avoidance of model misspecification and its unbiasedness for data missing completely at random or at random.

Methods

We extended the MMRM to cluster randomized trials by adding a random intercept for the cluster and undertook a simulation experiment to investigate statistical properties when data are missing at random. We simulated cluster randomized trial data where the outcome was continuous and measured at baseline and three post-intervention time points. We varied the numb

SUBMITTER: Bell ML 

PROVIDER: S-EPMC7006144 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature