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

Autor(es)

Prates, Marcos O. ^[1] ; Costa, Denise R. ^[2] ; Lachos, Victor H. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Fed Minas Gerais, Dept Stat, Belo Horizonte, MG - Brazil

^[2] Univ Estadual Campinas, Dept Stat, Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: STATISTICS AND COMPUTING; v. 24, n. 6, p. 1111-1123, NOV 2014.
• Citações Web of Science: 3

Resumo

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)

• Processo FAPESP: 11/17400-6 - Aplicações das distribuições de misturas da escala Skew-Normal em modelos de efeitos mistos
• Beneficiário: Víctor Hugo Lachos Dávila
• Modalidade de apoio: Auxílio à Pesquisa - Regular