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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 | Source: | 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 | Keywords: | additive model; deviance information criteria; multiplicative model; overdispersion | Document URI: | http://hdl.handle.net/1942/17793 | ISSN: | 0361-0918 | e-ISSN: | 1532-4141 | DOI: | 10.1080/03610918.2013.781629 | ISI #: | 000341525000012 | Rights: | Copyright © Taylor & Francis Group, LLC. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2015 |
Appears in Collections: | Research publications |
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12780.pdf | Peer-reviewed author version | 260.76 kB | Adobe PDF | View/Open |
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