WEN-CHUNG LEEWang L.-Y.2020-11-192020-11-1920090895-4356https://www.scopus.com/inward/record.uri?eid=2-s2.0-57449110597&doi=10.1016%2fj.jclinepi.2008.02.016&partnerID=40&md5=e578a4995e5f76d8d2310e019cb6ae09https://scholars.lib.ntu.edu.tw/handle/123456789/521855Objective: Genetic studies of complex human diseases rely heavily on the epidemiologic association paradigm, particularly the population-based case-control designs. This study aims to compare the matching effectiveness in terms of bias reduction between exposure matching and stratum matching. Study Design and Setting: Formulas for population stratification bias were derived. An index of matching effectiveness was constructed to compare the two types of matching. Results: It was found that exposure matching can paradoxically increase the magnitude of population stratification bias sometimes, whereas stratum matching can guarantee to reduce it. Conclusion: The authors propose two simple rules for genetic association studies: (a) to match on anything that helps to delineate population strata such as race, ethnicity, nationality, ancestry, and birthplace and (b) to match on an exposure only when it is a strong predictor of the disease and is expected to have great variation in prevalence across population strata. ? 2008 Elsevier Inc. All rights reserved.English[SDGs]SDG3article; controlled study; epidemiological data; external bias; gene; genetic association; genetic epidemiology; mathematical model; population exposure; priority journal; stratification; Algorithms; Bias (Epidemiology); Case-Control Studies; Disease; Epidemiologic Research Design; Genetics, Population; Humans; Matched-Pair Analysis; Models, Statistical; Population Groupsjournal article10.1016/j.jclinepi.2008.02.016186198102-s2.0-57449110597