title: Homogeneity test for correlated binary data.
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.
authors.affiliation: Department of Biostatistics, University at Buffalo, Buffalo, New York 14214, USA.
authors.forename: Changxing
authors.initials: C
authors.lastname: Ma
authors.affiliation: Department of Environmental and Occupational Health, School of Community Health Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA.
authors.forename: Guogen
authors.initials: G
authors.lastname: Shan
authors.affiliation: Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY 14203, USA.
authors.forename: Song
authors.initials: S
authors.lastname: Liu
mesh_terms: D000328:Adult; D000465:Algorithms; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted; D006801:Humans; D016013:Likelihood Functions; D009010:Monte Carlo Method; D012174:Retinitis Pigmentosa / Q000175:diagnosis* / Q000235:genetics; D055815:Young Adult