Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
---|---|
Data(s) |
20/10/2012
20/10/2012
2009
|
Resumo |
Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set. Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), Brazil Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) |
Identificador |
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, v.38, n.7, p.1447-1469, 2009 0361-0918 http://producao.usp.br/handle/BDPI/28961 10.1080/03610910902972310 |
Idioma(s) |
eng |
Publicador |
TAYLOR & FRANCIS INC |
Relação |
Communications in Statistics-simulation and Computation |
Direitos |
restrictedAccess Copyright TAYLOR & FRANCIS INC |
Palavras-Chave | #EM algorithm #Likelihood ratio #Null intercept errors-in-variables models #Score statistic #Wald statistic #MAXIMUM-LIKELIHOOD-ESTIMATION #REGRESSION #ALGORITHM #Statistics & Probability |
Tipo |
article original article publishedVersion |