Document Server@UHasselt >
Research >
Research publications >

Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/14380

Title: Double generalized linear model for tissue culture proportion data: a Bayesian perspective
Authors: Vieira, Afranio M. C.
Leandro, Roseli A.
Demetrio, Clarice G. B.
Molenberghs, Geert
Issue Date: 2011
Citation: JOURNAL OF APPLIED STATISTICS, 38 (8), p. 1717-1731
Abstract: Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.
Notes: [Vieira, Afranio M. C.] Univ Brasilia, ICC Ctr, Dept Estat, BR-70910900 Brasilia, DF, Brazil. [Leandro, Roseli A.; Demetrio, Clarice G. B.] Univ Sao Paulo ESALQ, Dept Ciencias Exatas, BR-13418900 Piracicaba, SP, Brazil. [Molenberghs, Geert] Univ Hasselt, I BioStat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert] Katholieke Univ Leuven, B-3590 Diepenbeek, Belgium. afranio@unb.br
URI: http://hdl.handle.net/1942/14380
DOI: 10.1080/02664763.2010.529875
ISI #: 000291464400012
ISSN: 0266-4763
Category: A1
Type: Journal Contribution
Validation: ecoom, 2012
Appears in Collections: Research publications

Files in This Item:

Description SizeFormat
Published version255.41 kBAdobe PDF
Peer-reviewed author version360.99 kBAdobe PDF

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