Bayesian analysis for a skew extension of the multivariate null intercept measurement error model

V. G. Cancho, Reiko Aoki and V. H. Lachos

Journal of Applied Statistics, 2008, vol. 35, issue 11, 1239-1251

Abstract: Skew-normal distribution is a class of distributions that includes the normal distributions as a special case. In this paper, we explore the use of Markov Chain Monte Carlo (MCMC) methods to develop a Bayesian analysis in a multivariate, null intercept, measurement error model [R. Aoki, H. Bolfarine, J.A. Achcar, and D. Leao Pinto Jr, Bayesian analysis of a multivariate null intercept error-in-variables regression model, J. Biopharm. Stat. 13(4) (2003b), pp. 763-771] where the unobserved value of the covariate (latent variable) follows a skew-normal distribution. The results and methods are applied to a real dental clinical trial presented in [A. Hadgu and G. Koch, Application of generalized estimating equations to a dental randomized clinical trial, J. Biopharm. Stat. 9 (1999), pp. 161-178].

Keywords: Skew-normal distribution; Gibbs algorithm; skewness; multivariate null intercepts model; measurement error (search for similar items in EconPapers)
Date: 2008
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DOI: 10.1080/02664760802319667

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