Are most published research findings false in a continuous universe?
Fig 3
Type S error rate (i.e. published estimates with the wrong sign) as a function of the prevalence of true effects, statistical power and bias for (A) Two Peaks, (B) Overlapping Peaks, (C) Two Normals and (D) Single Normal effect size distributions.
The rate corresponds to the percent of published (i.e. statistically significant) estimates that are in the opposite direction of the true effect. Each point corresponds to the sign error rate from a simulation with 5,000 published findings. In each panel, graphs correspond to 20%, 50% and 80% power from left to right. Blue, red and green curves correspond to bias of 0, 0.2 and 0.6, respectively. Prevalence ranges vary among scenarios, as for some distributions some prevalences cannot be achieved without changing other parameters.