Hierarchical Bayesian modeling of heterogeneous outcome variance in cluster randomized trials.

ABSTRACT:

Background

Heterogeneous outcome correlations across treatment arms and clusters have been increasingly acknowledged in cluster randomized trials with binary endpoints, where analytical methods have been developed to study such heterogeneity. However, cluster-specific outcome variances and correlations have yet to be studied for cluster randomized trials with continuous outcomes.

Methods

This article proposes models fitted in the Bayesian setting with hierarchical variance structure to quantify heterogeneous variances across clusters and explain it with cluster-level covariates when the outcome is continuous. The models can also be extended to analyzing heterogeneous variances in individually randomized group treatment trials, with arm-specific cluster-level covariates, or i

SUBMITTER: Tong G 

PROVIDER: S-EPMC11233424 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature