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Measurements are generally collected as unilateral or bilateral data inclinical trials or observational studies. For example, in ophthalmologicstudies, statistical tests are often based on one or two eyes of an individual.For bilateral data, recent literatures have shown some testing procedures thattake into account the intra-class correlation between two eyes of the sameperson. Ma et al. (2015) investigated three testing procedures under Rosner'smodel. In this paper, we extend Ma's work for bilateral data to combinedbilateral and unilateral data. The proposed procedures are based on thelikelihood estimate algorithm derived from the root of 4th order polynomialequations and fisher scoring iterations. Simulation studies are performed tocompare the testing procedures under different parameter configurations. Theresult shows that score test has satisfactory type I error rates and powers.Therefore, we recommend score test for testing the equality of proportions. Weillustrate the application of the proposed methods with a double-blindrandomized clinical trial.

Testing the Equality of Proportions for Combined Unilateral and Bilateral Data