Traditionally, statistical power was viewed as relevant to research planning but not evaluation of completed research. However, following discussions of high false finding rates (FFRs) associated with low statistical power, the assumed level of statistical power has become a key criterion for research acceptability. Yet, the links between power and false findings are not as straightforward as described. Assumptions underlying FFR calculations do not reflect research realities in personality and social psychology. Even granting the assumptions, the FFR calculations identify important limitations to any general influences of statistical power. Limits for statistical power in inflating false findings can also be illustrated through the use of FFR calculations to (a) update beliefs about the null or alternative hypothesis and (b) assess the relative support for the null versus alternative hypothesis when evaluating a set of studies. Taken together, statistical power should be de-emphasized in comparison to current uses in research evaluation.
