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Stat Med. 2013 Jun 30;32(14):2390-405. doi: 10.1002/sim.5691. Epub 2012 Dec 12.

Distribution-free models for longitudinal count responses with overdispersion and structural zeros.

Author information

1
Department of Biostatistics and Computational Biology, University of Rochester, 601 Elmwoord Ave, Rochester, NY 14642, USA. qyuflow@gmail.com

Abstract

Overdispersion and structural zeros are two major manifestations of departure from the Poisson assumption when modeling count responses using Poisson log-linear regression. As noted in a large body of literature, ignoring such departures could yield bias and lead to wrong conclusions. Different approaches have been developed to tackle these two major problems. In this paper, we review available methods for dealing with overdispersion and structural zeros within a longitudinal data setting and propose a distribution-free modeling approach to address the limitations of these methods by utilizing a new class of functional response models. We illustrate our approach with both simulated and real study data.

PMID:
23239019
PMCID:
PMC3806502
DOI:
10.1002/sim.5691
[Indexed for MEDLINE]
Free PMC Article
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