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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Generalized linear mixed models for correlated binary data with t-link

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Prates, Marcos O. [1] ; Costa, Denise R. [2] ; Lachos, Victor H. [2]
Total Authors: 3
[1] Univ Fed Minas Gerais, Dept Stat, Belo Horizonte, MG - Brazil
[2] Univ Estadual Campinas, Dept Stat, Campinas, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: STATISTICS AND COMPUTING; v. 24, n. 6, p. 1111-1123, NOV 2014.
Web of Science Citations: 3

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. (AU)

FAPESP's process: 11/17400-6 - Applications of the scale mixture of Skew-Normal distributions in linear mixed effects models
Grantee:Víctor Hugo Lachos Dávila
Support type: Regular Research Grants