Simple formulas for gauging the potential impacts of population stratification bias
Journal
American Journal of Epidemiology
Journal Volume
167
Journal Issue
1
Pages
86-89
Date Issued
2008
Author(s)
Wang L.-Y.
Abstract
The case-control study design is popular for genetic association studies of complex human diseases. However, case-control studies may suffer from bias due to population stratification. In this paper, the authors present simple formulas that can set a limit to the havoc population stratification bias can wreak (the lower and upper bounds of the confounding rate ratio and the upper bound of the type I error rate). The authors demonstrate applications of these formulas using two examples. The formulas can help researchers make more prudent interpretations of their (potentially biased) results. ? The Author 2007. Published by the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
SDGs
Other Subjects
data interpretation; design; epidemiology; genetics; public health; analytical error; article; confounding variable; genetic association; genetic polymorphism; genetic susceptibility; genotype; population based case control study; statistical analysis; Bias (Epidemiology); Case-Control Studies; Confounding Factors (Epidemiology); Data Interpretation, Statistical; Genetics, Population; Humans; Models, Statistical; Odds Ratio
Type
journal article