To test whether a limited number of AIMs can correct for false positive results observed in case-control studies due to population stratification we modeled three population specific loci as disease phenotypes. The modeling was done in the following step-wise manner independently for each surrogate phenotype: 1) surrogate cases and controls (with available SNP genotypes on Illumina 300 K platform) were chosen on the basis of genotypes for a population specific marker; 2) 200 K SNPs that passed quality control filters in the surrogate case-control sample sets were tested for association using the HelixTree software package; 3) significantly associated markers (by Armitage χ2 test, χ2 ≥26.6. p≤0.05 with Bonferroni correction for 200,000 tests) in or near the locus designating the surrogate phenotype are defined as true positive signal, while significantly associated SNPs outside the locus are defined as false positives; 4) six to ten SNPs with the strongest false positive associations and a similar number of true positive associations with χ2 values comparable to the false positives were selected for further analysis; 5) the genotypes for the chosen true and false
