Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/81082
Type: Artigo
Title: Linear mixed models for skew-normal independent bivariate responses with an application to periodontal disease
Author: Bandyopadhyay, Dipankar
Lachos, Victor H.
Abanto-Valle, Carlos A.
Ghosh, Pulak
Abstract: Bivariate clustered (correlated) data often encountered in epidemiological and clinical research are routinely analyzed under a linear mixed model (LMM) framework with underlying normality assumptions of the random effects and within-subject errors. However, such normality assumptions might be questionable if the data set particularly exhibits skewness and heavy tails. Using a Bayesian paradigm, we use the skew-normal/independent (SNI) distribution as a tool for modeling clustered data with bivariate non-normal responses in an LMM framework. The SNI distribution is an attractive class of asymmetric thick-tailed parametric structure which includes the skew-normal distribution as a special case. We assume that the random effects follow multivariate SNI distributions and the random errors follow SNI distributions which provides substantial robustness over the symmetric normal process in an LMM framework. Specific distributions obtained as special cases, viz, the skew-t, the skew-slash and the skew-contaminated normal distributions are compared, along with the default skew-normal density. The methodology is illustrated through an application to a real data which records the periodontal health status of an interesting population using periodontal pocket depth (PPD) and clinical attachment level (CAL). Copyright (c) 2010 John Wiley & Sons, Ltd.
Bivariate clustered (correlated) data often encountered in epidemiological and clinical research are routinely analyzed under a linear mixed model (LMM) framework with underlying normality assumptions of the random effects and within-subject errors. Howev
Subject: Distribuição normal assimétrica
Métodos MCMC (Estatística)
Modelos lineares (Estatística)
Influência local (Estatística)
Inferência bayesiana
Doenças periodontais
Country: Reino Unido
Editor: John Wiley & Sons
Citation: Statistics In Medicine. John Wiley & Sons Ltd, v. 29, n. 25, n. 2643, n. 2655, 2010.
Rights: fechado
Identifier DOI: 10.1002/sim.4031
Address: https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.4031
Date Issue: 2010
Appears in Collections:IMECC - Artigos e Outros Documentos

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