TY - JOUR
T1 - Reducing population stratification bias
T2 - stratum matching is better than exposure
AU - Lee, Wen Chung
AU - Wang, Liang Yi
N1 - Funding Information:
This paper is partly supported by grants from the National Science Council, Taiwan, Republic of China (NSC 95-2314-B-002-242, NSC 95-3114-P-002-005-Y, and NSC 96-2314-B-002-143).
PY - 2009/1
Y1 - 2009/1
N2 - Objective: 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.
AB - Objective: 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.
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U2 - 10.1016/j.jclinepi.2008.02.016
DO - 10.1016/j.jclinepi.2008.02.016
M3 - Article
C2 - 18619810
AN - SCOPUS:57449110597
SN - 0895-4356
VL - 62
SP - 62
EP - 66
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
IS - 1
ER -