HOMOGENEITY TEST FOR CORRELATED DATA IN OPHTHALMOLOGIC STUDIES
Changxing Ma
Introduction
In ophthalmologic studies, measurements obtained from both eyes
of an individual are often highly correlated. Ignoring the correlation could lead
to incorrect inferences. Donner (1989) proposed a parametric model and a test statistic for testing
homogeneity of proportions among g groups accounting for inter-class correlation, however, the maximum likelihood estimates
(MLEs) and likelihood-based tests were not given.
Ma (2013) derived a efficient algorithm for MLE under constant common correlation model and three testing procedures for this problem.
This calculator provides a user-friendly interface to use this methodology.
Calculator
Please input your data into box below, or simulate data On Off
True Parameters:
(π1, π2, ..., πg)
(m1, m2, ..., mg)
(n1, n2, ..., ng)
Common correlation ρ
3 × g matrix for bilateral patients followed by 2 × g matrix for unilateral patients
