A marginalized zero-inflated Poisson regression model with random effects

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

Journal of the Royal Statistical Society Series C, 2015, vol. 64, issue 5, 815-830

Abstract: type="main" xml:id="rssc12104-abs-0001">

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.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1111/rssc.2015.64.issue-5 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:64:y:2015:i:5:p:815-830

Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876

Access Statistics for this article

Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith

More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().