Bayesian multilevel multivariate logistic regression for superiority decision-making under observable treatment heterogeneity.

ABSTRACT:

Background

In medical, social, and behavioral research we often encounter datasets with a multilevel structure and multiple correlated dependent variables. These data are frequently collected from a study population that distinguishes several subpopulations with different (i.e., heterogeneous) effects of an intervention. Despite the frequent occurrence of such data, methods to analyze them are less common and researchers often resort to either ignoring the multilevel and/or heterogeneous structure, analyzing only a single dependent variable, or a combination of these. These analysis strategies are suboptimal: Ignoring multilevel structures inflates Type I error rates, while neglecting the multivariate or heterogeneous structure masks detailed insights.

Methods

To analyze suc

SUBMITTER: Kavelaars X 

PROVIDER: S-EPMC10552398 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature