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A Marginalized Zero-Inflated Poisson Regression Model with Random Effects

Citation

Long, D. Leann; Preisser, John S.; Herring, Amy H.; & Golin, Carol Elaine (2015). A Marginalized Zero-Inflated Poisson Regression Model with Random Effects. Journal of the Royal Statistical Society, Series C (Applied Statistics), 64(5), 815-830. PMCID: PMC4664481

Abstract

Public health research often concerns relationships between exposures and correlated count outcomes. When counts exhibit more 0s than expected under Poisson sampling, the zero-inflated Poisson (ZIP) model with random effects may be used. However, the latent class formulation of the ZIP model can make marginal inference on the population sampled challenging. The paper presents a marginalized ZIP model with random effects to model directly the mean of the mixture distribution consisting of ‘susceptible’ individuals and excess 0s, providing straightforward inference for overall exposure effects. Simulations evaluate finite sample properties, and the new methods are applied to a motivational interviewing-based safer sex intervention trial, designed to reduce the number of unprotected sexual acts, to illustrate the new methods.

URL

http://dx.doi.org/10.1111/rssc.12104

Reference Type

Journal Article

Year Published

2015

Journal Title

Journal of the Royal Statistical Society, Series C (Applied Statistics)

Author(s)

Long, D. Leann
Preisser, John S.
Herring, Amy H.
Golin, Carol Elaine

PMCID

PMC4664481