A Bayesian beta-binomial piecewise growth mixture model for longitudinal overdispersed binomial data.

ABSTRACT: In a recent 12-week smoking cessation trial, varenicline tartrate failed to show significant improvements in enhancing end-of-treatment abstinence when compared with placebo among adolescents and young adults. The original analysis aimed to assess the average effect across the entire population using timeline followback methods, which typically involve overdispersed binomial counts. We instead propose to investigate treatment effect heterogeneity among latent classes of participants using a Bayesian beta-binomial piecewise linear growth mixture model specifically designed to address longitudinal overdispersed binomial responses. Within each class, we fit a piecewise linear beta-binomial mixed model with random changepoints for each study group to detect critical windows of treatment effica

SUBMITTER: Wen CC 

PROVIDER: S-EPMC12495558 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature