Excess significance testing evaluates whether the number of statistically significant results in a corpus of studies it too high, under some plausible assumptions about the magnitude of the true effect size [19]. The Ioannidis test [19] can be applied to meta-analyses of multiple studies and also to larger fields and disciplines where many meta-analyses are compiled. The number of expected studies with nominally statistically significant results is estimated by summing the calculated power of all the considered studies. Simulations suggest that the most appropriate assumption is the effect size of the largest study in each meta-analysis [20].
