www.uhasselt.be
DSpace

Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/17793

Title: Comparison of Additive and Multiplicative Bayesian Models for Longitudinal Count Data With Overdispersion Parameters: A Simulation Study
Authors: Aregay, Mehreteab
Shkedy, Ziv
Molenberghs, Geert
Issue Date: 2015
Citation: COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 44 (2), p. 454-473
Abstract: In applied statistical data analysis, overdispersion is a common feature. It can be addressed using both multiplicative and additive random effects. A multiplicative model for count data incorporates a gamma random effect as a multiplicative factor into the mean, whereas an additive model assumes a normally distributed random effect, entered into the linear predictor. Using Bayesian principles, these ideas are applied to longitudinal count data, based on the so-called combined model. The performance of the additive and multiplicative approaches is compared using a simulation study.
Notes: Molenberghs, G (reprint author), Hasselt Univ, I BioStat, Agoralaan 1, B-3590 Diepenbeek, Belgium. Geert.Molenberghs@uhasselt.be
URI: http://hdl.handle.net/1942/17793
DOI: 10.1080/03610918.2013.781629
ISI #: 000341525000012
ISSN: 0361-0918
Category: A1
Type: Journal Contribution
Validation: ecoom, 2015
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
Published version585.1 kBAdobe PDF
Peer-reviewed author version270.61 kBAdobe PDF

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.