A Bayesian zero-inflated beta-binomial model for longitudinal data with group-specific changepoints.

ABSTRACT: Timeline followback (TLFB) is often used in addiction research to monitor recent substance use, such as the number of abstinent days in the past week. TLFB data usually take the form of binomial counts that exhibit overdispersion and zero inflation. Motivated by a 12-week randomized trial evaluating the efficacy of varenicline tartrate for smoking cessation among adolescents, we propose a Bayesian zero-inflated beta-binomial model for the analysis of longitudinal, bounded TLFB data. The model comprises a mixture of a point mass that accounts for zero inflation and a beta-binomial distribution for the number of days abstinent in the past week. Because treatment effects appear to level off during the study, we introduce random changepoints for each study group to reflect group-specific chang

SUBMITTER: Wen CC 

PROVIDER: S-EPMC12661921 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature