Affordable Access

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

Authors
Journal
Journal of Applied Statistics
0266-4763
Publisher
Informa UK (Taylor & Francis)
Publication Date
Keywords
  • Skew-Normal Distribution
  • Gibbs Algorithm
  • Skewness
  • Multivariate Null Intercepts Model
  • Measurement Error

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].

There are no comments yet on this publication. Be the first to share your thoughts.