Testing the Equality of Proportions for Combined Unilateral and Bilateral Data

Abstract: Measurements are generally collected as unilateral or bilateral data in clinical trials or observational studies. For example, in ophthalmologic studies, statistical tests are often based on one or two eyes of an individual. For bilateral data, recent literatures have shown some testing procedures that take into account the intra-class correlation between two eyes of the same person. Ma et al. (2015) investigated three testing procedures under Rosner's model. In this paper, we extend Ma's work for bilateral data to combined bilateral and unilateral data. The proposed procedures are based on the likelihood estimate algorithm derived from the root of 4th order polynomial equations and fisher scoring iterations. Simulation studies are performed to compare the testing procedures under different parameter configurations. The result shows that score test has satisfactory type I error rates and powers. Therefore, we recommend score test for testing the equality of proportions. We illustrate the application of the proposed methods with a double-blind randomized clinical trial.