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Activity Number: 338 - SPEED: Biostatistical Methods, Application, and Education, Part 1
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract #307386
Title: A Bayesian Zero Inflated Binomial Model for Repeated Measures Count Data
Author(s): Benjamin W. Rogers*
Companies: UCLA
Keywords: Bayesian inference; longitudinal data; binomial distribution; zero-inflated

Substance use data is often complicated by the presence of a disproportionate number of zeros over standard models. A popular approach to this problem is the use of zero inflated distributions, such as the zero inflated binomial (ZIB). Motivated by a longitudinal study measuring days of substance use in the last 3 months, we present a Bayesian approach to repeated measures zero-inflated binomial models. We employ a first order antedependence covariance structure for the random effects, which allows for different correlations between different pairs of adjacent time points, to account for unequal spacing in the follow up visits.

Authors who are presenting talks have a * after their name.

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