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Homogeneity test for correlated binary data

  • University of Nevada, Las Vegas

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

In ophthalmologic studies, measurements obtained from both eyes of an individual are often highly correlated. Ignoring the correlation could lead to incorrect inferences. An asymptotic method was proposed by Tang and others (2008) for testing equality of proportions between two groups under Rosner's model. In this article, we investigate three testing procedures for general g ≥ 2 groups. Our simulation results show the score testing procedure usually produces satisfactory type I error control and has reasonable power. The three test procedures get closer when sample size becomes larger. Examples from ophthalmologic studies are used to illustrate our proposed methods.

Original languageEnglish
Article numbere0124337
JournalPLOS ONE
Volume10
Issue number4
DOIs
StatePublished - Apr 21 2015

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