title: Mixture of normal distributions in multivariate null intercept measurement error model.
abstract: In this paper we propose the use of a multivariate null intercept measurement error model, where the true unobserved value of the covariate follows a mixture of two normal distributions. The proposed model is applied to a dental clinical trial presented in Hadgu and Koch (1999). A Bayesian approach is considered and a Gibbs Sampler is used to perform the computations.
authors.affiliation: Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, São Paulo, Brazil. reikoi@icmc.sc.usp.br
authors.forename: Reiko
authors.initials: R
authors.lastname: Aoki
authors.forename: Dorival Leão
authors.initials: DL
authors.lastname: Pinto Júnior
authors.forename: Jorge Alberto
authors.initials: JA
authors.lastname: Achcar
authors.forename: Heleno
authors.initials: H
authors.lastname: Bolfarine
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002986:Clinical Trials as Topic; D003773:Dental Plaque / Q000188:drug therapy; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D009067:Mouthwashes / Q000627:therapeutic use; D015999:Multivariate Analysis; D012107:Research Design
chemical_list: D009067:Mouthwashes