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Title: | Double generalized linear model for tissue culture proportion data: a Bayesian perspective | Authors: | CORREA VIEIRA, Afranio Marcio Leandro, Roseli A. DEMETRIO, Clarice MOLENBERGHS, Geert |
Issue Date: | 2011 | Publisher: | ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD | Source: | 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 | Keywords: | Bayesian data analysis; generalized linear models; tissue culture; Markov Chain Monte Carlo; binomial distribution; Gibbs sampling; random effects;Bayesian data analysis; generalized linear models; tissue culture; Markov Chain Monte Carlo; binomial distribution; Gibbs sampling; random effects | Document URI: | http://hdl.handle.net/1942/14380 | ISSN: | 0266-4763 | e-ISSN: | 1360-0532 | DOI: | 10.1080/02664763.2010.529875 | ISI #: | 000291464400012 | Rights: | © 2011 Taylor & Francis | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2012 |
Appears in Collections: | Research publications |
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vieira2011.pdf Restricted Access | Published version | 255.41 kB | Adobe PDF | View/Open Request a copy |
ArtigoDglmBayesianoV9.pdf | Peer-reviewed author version | 349.32 kB | Adobe PDF | View/Open |
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