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One‐Sided Test to Assess Correlation in Linear Logistic Models using Estimating Equations
Author(s) -
Paula Gilberto A.,
Artes Rinaldo
Publication year - 2000
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200010)42:6<701::aid-bimj701>3.0.co;2-z
Subject(s) - mathematics , statistics , univariate , score test , logistic regression , generalized estimating equation , binomial test , correlation , binomial regression , binomial (polynomial) , likelihood ratio test , covariate , multivariate statistics , statistical hypothesis testing , null hypothesis , binary data , binary number , negative binomial distribution , poisson distribution , arithmetic , geometry
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.