Homogeneity Test for Correlated Binary Data
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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.
Eyes; Test statistics; Retinitis pigmentosa; Blindness; Monte Carlo method; Polynomials; Statistical distributions; Randomized controlled trials
Homogeneity Test for Correlated Binary Data.
PLOS One, 10(4),