RESPONSE: Re: Assessing the Probability That a Positive Report is False: An Approach for Molecular Epidemiology Studies

Extract

Dr. Dubben notes that a study with higher statistical power will have a lower false-positive report probability (FPRP) than a study with lower statistical power, as seen in equation 1 and in figures 1 and 2 of our original paper ( 1 ). He is puzzled, however, by figure 5 ( 1 ), which shows FPRP increasing with increasing statistical power.

Our paper's figure 5 ( 1 ) shows the reduction in statistical power with fixed sample size from demanding stronger evidence for calling a study positive, whether by an FPRP or P- value criterion. By contrast, sample size is not fixed in figures 1, 2, and 3 ( 1 ), which show the influence of prior probability and of statistical power, manifested through sample size, on FPRP. When sample size is fixed, there is an additional constraint implicit in equation 2 because varying α has a direct effect on statistical power. On the other hand, all the variables on the right side of equation 1 are free to vary independently when sample size is not fixed.