If the researchers assume based on Weisler et al., (2012) a placebo response rate of 30% and a quetiapine 150-300 mg/day response rate of 50% (and N = 1570), a simulated Cox regression predicting overall treatment response, which the researchers ran in Stata 13, yielded a hazard ratio of 1.6 (p < .001). The Stpower command showed that a Cox regression and overall response rate of 42% (50% treatment, 30% placebo) could detect a hazard ratio of 1.6 at a=.05 with 80% power with an N value of 339. It is usually recommended that to detect a subgroup treatment effect with adequate power, the minimum required sample size to detect a treatment response be multiplied by four (Brookes et al., 2004). Therefore the researchers would consider a subgroup analysis with a sample of 1570 (> 4x 339) to be adequate to detect a potential interaction if it exists. The researchers also ran a second simulated Cox regression with a sample of 1570 (30% melancholic; 70% nonmelancholic, and assuming the ratio of 935 treatment:635 placebo would also be true of each subgroup) with an overall response rate of 42%, a 30% response rate in placebo groups (regardless of melancholia status), and a 10% response rate difference between the melancholic treatment group and nonmelancholic treatment group (which, given the predicted number of overall responses in treatment group, leaves a rate of 47% in the nonmelancholic treatment group and 57% in the melancholic treatment group) and found that the tested interaction was statistically significant such that in the treatment group the odds of response was higher for those with melancholic depression vs nonmelancholic depression (HR 1.7, p < .001). Therefore, the researchers consider the proposed analysis appropriately powered to detect a small subgroup treatment effect assuming the predicted overall treatment effect (based on Weisler et al., 2012).