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PubMed · 8800607

A SAS macro for stepwise correlated binary regression.

I F Nuamah·Y Qu·S B Amini
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Abstract

Several regression methods have been proposed for the analysis of correlated binary data, but none deals with the selection of covariates when there exist a large number of potentially relevant covariates. We present a SAS macro based on a stepwise selection procedure for the analysis of correlated binary data. Using regression methods based on generalized estimating equations originally proposed by Liang and Zeger and extended by Prentice, we describe a score test for forward selection, a Wald's test for backward elimination, and a test for model adequacy based on generalized scores. The methodology and the accompanying computer macro program written in SAS IML are illustrated with data from a prospective study of functional decline in the activities of daily living in a group of elderly patients.

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Activities of Daily LivingAgedAged, 80 and overBiometryFemaleHumansLongitudinal StudiesMaleModels, StatisticalProspective StudiesRegression AnalysisSoftwareJournal ArticleResearch Support, Non-U.S. Gov't

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I F Nuamah, Y Qu, S B Amini. 1996. A SAS macro for stepwise correlated binary regression.. https://doi.org/10.1016/0169-2607(96)01718-x

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