Screening for data clustering in multicenter studies: the residual intraclass correlation

Abstract

In multicenter studies, center-specific variations in measurements may arise for various reasons, such as low interrater reliability, differences in equipment, deviations from the protocol, sociocultural characteristics, and differences in patient populations due to e.g. local referral patterns. The aim of this research is to derive measures for the degree of clustering. We present a method to detect heavily clustered variables and to identify physicians with outlying measurements.