Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/89632
Type: Artigo de periódico
Title: Generalized Linear Mixed Models For Correlated Binary Data With T-link
Author: Prates M.O.
Costa D.R.
Lachos V.H.
Abstract: A critical issue in modeling binary response data is the choice of the links. We introduce a new link based on the Student's t-distribution (t-link) for correlated binary data. The t-link relates to the common probit-normal link adding one additional parameter which controls the heaviness of the tails of the link. We propose an interesting EM algorithm for computing the maximum likelihood for generalized linear mixed t-link models for correlated binary data. In contrast with recent developments (Tan et al. in J. Stat. Comput. Simul. 77:929-943, 2007; Meza et al. in Comput. Stat. Data Anal. 53:1350-1360, 2009), this algorithm uses closed-form expressions at the E-step, as opposed to Monte Carlo simulation. Our proposed algorithm relies on available formulas for the mean and variance of a truncated multivariate t-distribution. To illustrate the new method, a real data set on respiratory infection in children and a simulation study are presented. © 2013 Springer Science+Business Media New York.
Editor: 
Rights: fechado
Identifier DOI: 10.1007/s11222-013-9423-3
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-84889965810&partnerID=40&md5=fe1c3dacd08f762ac58413963dc49605
Date Issue: 2013
Appears in Collections:Unicamp - Artigos e Outros Documentos

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