Statistical methods for the bilateral correlated data

Bilateral correlated data are often encountered in medical researches such as ophthalmologic (or otolaryngologic) studies, in which each unit contributes information from paired organs to the data analysis. Measurements obtained from paired organs of a subject are generally highly correlated, whereas many statistical tests assume observations in a sample are independent. Previous studies showed that the statistical inference for bilateral correlated data ignoring the presence of intra-class correlation could lead to inflated significance levels. Various statistical methods have been developed to tackle this intra-class correlation on the bilateral correlated data analysis. Furthermore, in some studies, it is very important to adjust the effect of confounder on statistical inferences, since either ignoring the intra-class correlation or confounding effect may lead to biased results. In this paper, we review these methods, discuss the applications and provide statistical advice.