Please use this identifier to cite or link to this item: https://repositorio.insper.edu.br/handle/11224/4009
Type: Artigo Científico
Title: One-Sided Test to Assess Correlation in Linear Logistic Models using Estimating Equations
Author: Artes, Rinaldo
Paula, Gilberto Alvarenga
Publication Date: 2000
Abstract: A score-type test is proposed for testing the hypothesis of independent binary random variables against positive correlation in linear logistic models with sparse data and cluster specific covariates. The test is developed for univariate and multivariate one-sided alternatives. The main advantage of using score test is that it requires estimation of the model only under the null hypothesis, that in this case corresponds to the binomial maximum likelihood fit. The score-type test is developed from a class of estimating equations with block-diagonal structure in which the coefficients of the linear logistic model are estimated simultaneously with the correlation. The simplicity of the score test is illustrated in two particular examples.
Keywords (english terms): Correlated binary variables
extra-binomial variation
generalized estimating equations
modeling overdispersation
one-sided test
quasi-likelihood
Language: Inglês
CNPq Area: Ciências Exatas e da Terra
Copyright: O INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITOR
Notes: Texto completo
Appears in Collections:Coleção de Artigos

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