Distribution‐free models for longitudinal count responses with overdispersion and structural zeros. (12th December 2012)

• Record Type: Journal Article
• Authors: Yu, Q.; Chen, R.; Tang, W.; He, H.; Gallop, R.; Crits‐Christoph, P.; Hu, J.; Tu, X.M.
• Is Part Of: Statistics in medicine. Volume 32:Number 14(2013)
• Page Start: 2390
• Page End: 2405
• Publication Date: 2012-12-12
• Subjects: Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.5691
• Languages: English
• ISSNs: 0277-6715

Abstract

<abstract abstract-type="main" id="sim5691-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p id="sim5691-para-0001">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. Copyright © 2012 John Wiley &amp; Sons, Ltd.</p> </abstract>