A Marginalized Zero-Inflated Poisson Regression Model with Random Effects. Issue 5 (30th April 2015)

• Record Type: Journal Article
• Authors: Leann Long, D.; Preisser, John S.; Herring, Amy H.; Golin, Carol E.
• Is Part Of: Journal of the Royal Statistical Society. Volume 64:Issue 5(2015:Nov.)
• Page Start: 815
• Page End: 830
• Publication Date: 2015-04-30
• Subjects: Marginalized models -- Repeated measures -- Unprotected intercourse -- Zero inflation; Statistics -- Periodicals; 519.5
• DOI: 10.1111/rssc.12104
• Languages: English
• ISSNs: 0035-9254

Abstract

Summary: 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.