Models for Zero-Inflated and Overdispersed Correlated Count Data: An Application to Cigarette Use.

ABSTRACT:

Introduction

Count outcomes in tobacco research are often analyzed with the Poisson distribution. However, they often exhibit features such as overdispersion (variance larger than expected) and zero inflation (extra zeros) that violate model assumptions. Furthermore, longitudinal studies have repeated measures that generate correlated counts. Failure to account for overdispersion, zero inflation, and correlation can yield incorrect statistical inferences. Thus, it is important to familiarize researchers with proper models for such data.

Aims and methods

Poisson and Negative Binomial models with correlated random effects with and without zero inflation are presented. The illustrative data comes from a study comparing a mindfulness training app (Craving to Quit [C2Q], n = 60)

SUBMITTER: Pittman B 

PROVIDER: S-EPMC10077942 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature