534 – Contributed Poster Presentations: Section on Statistics in Epidemiology
False Positives and Population Stratification
Renfang Jiang
Michigan Technological University
Jianping Dong
Michigan Technological University
We will assess the seriousness of population stratification, and quantitatively study the bias caused by population stratification. In a case-control design, we compare chi-square statistics from a structured population (a union of two subpopulations) and a homogeneous population with the same prevalence and allele frequencies. We provide an explicit formula to calculate the chi-square statistics from 17 parameters, such as proportions of subpopulation, allele frequencies in subpopulations, etc. Each parameter takes a random value in a chosen range. We then calculate the likelihood of getting opposite conclusions in the structured and the homogeneous populations. This is the likelihood of having false positives caused by population stratification. Our results show that even though each parameter is allowed to vary within a wide range, the possibility of getting false positives is small. It is almost always smaller than 10%, and sometimes it is smaller than 2%. Sample sizes have a significant effect on the likelihood of false positive caused by population stratification. The larger the sample size is, the more likely to have false positive.