A robust Bayesian approach to null intercept measurement error model with application to dental data

Autor(es)

Ghosh, Pulak ^{[1, 2]} ; Bayes, C. L. ^[3] ; Lachos, V. H. ^[4]

Afiliação do(s) autor(es)

^[1] Emory Univ, Dept Biostat, Atlanta, GA 30322 - USA

^[2] Emory Univ, Winship Canc Inst, Atlanta, GA 30322 - USA

^[3] Univ Sao Paulo, Dept Estatist, IME, Sao Paulo - Brazil

^[4] Univ Estadual Campinas, Dept Estatist, IMECC, Campinas, SP - Brazil

• Tipo de documento: Artigo Científico
• Fonte: COMPUTATIONAL STATISTICS & DATA ANALYSIS; v. 53, n. 4, p. 1066-1079, FEB 15 2009.
• Citações Web of Science: 3

Resumo

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved. (AU)

• Processo FAPESP: 04/14721-2 - Inferencia sob a distribuicao multivariada t-assimetrica.
• Beneficiário: Cristian Luis Bayes Rodriguez
• Modalidade de apoio: Bolsas no Brasil - Doutorado
• Processo FAPESP: 07/03140-7 - Local Influence analysis of skew-normal / independent distributions
• Beneficiário: Víctor Hugo Lachos Dávila
• Modalidade de apoio: Auxílio à Pesquisa - Reunião - Exterior