Power analysis was conducted using the continuous outcome design option in Quanto (Gauderman, 2002a,b, 2003). Tests estimated the power to detect genetic effects between each of the SNPs (i.e., rs1391166 and rs1497571) and a continuous outcome (i.e., drinking and level of response to alcohol) in this sample of 124 unrelated individuals. Specifically, we allowed for the following in the power calculations for this study: (1) allele frequency of 0.50 (consistent with the observed minor allele frequencies in this sample); (2) the candidate locus to account for at least 1 % of the variance in the dependent variable with the estimated R2 ranging between 0.01 and 0.08; and (3) dominant gene action. We estimated power at 2 α-levels, 0.05 and 0.01, to assess the changes in statistical power resulting from possible corrections for Type I error. As shown in Table 2, at an α-level of 0.05, a dominant locus accounting for 6% or more of the overall variance would be detectable with better than 79% power. Conversely, at an α-level of 0.01, none of the power estimates for R2 ranging between 0.01 and 0.08 were ≥0.80, which is the recommended threshold (Cohen, 1988,1992).
