Examining Tables 6 and 7 reveals that the largest effect sizes are reported by studies with the smallest samples. In fact, sample size is inversely correlated with the magnitude of effect obtained. Unsurprisingly, only those studies with the largest samples obtained small effects; large samples are necessary in order to provide adequate power to detect such effects, which is precisely why they are needed (see Table 3). In addition, however, what is most striking about the studies with large samples is what they do not report: large effects. This is obviously not due to lack of power. That studies with the largest samples have not obtained large effects argues that the large effects from studies with small samples are almost certainly due to sampling variation or allelic stratification and are not true associations. To put this another way, a large effect size should be disquieting rather than reassuring; it almost surely signals that a finding is a false positive rather than confirming that it is real.
