In a recent article, Killeen (2005) proposed the statistic prep, the probability of replicating an effect, as an alternative to traditional null-hypotheses significant tests (NHST). In this article, two experiments were conducted and their analytical results based on prep and traditional p values were compared: non-significant results based on p values were reinterpreted as meaningful results in light of power analysis, calculating the effect size and prep value. The tendency of p value analyses not to reveal non-significant results (i.e. the file drawer problem) and the improvement of decision-making methods are discussed.
