Benjamin et al. Nature Human Behavior 2, 6–10 proposed decreasing the significance level by an order of magnitude to improve the replicability of psychology. This modest, practical proposal has been widely criticized, and its prospects remain unclear. This article defends this proposal against these criticisms and highlights its virtues.

‘Dira’ is a novel experimental paradigm to record combinations of behavioural and metacognitive measures for the creative process. This task allows assessing chronological and chronometric aspects of the creative process directly and without a detour through creative products or proxy phenomena. In a study with 124 participants we show that (a.) people spend more time attending to selected versus rejected potential solutions, (b.) there is a clear connection between behavioural patterns and self-reported measures, (c.) the reported intensity of Eureka experiences (...) is a function of interaction time with potential solutions, and (d.) experiences of emerging solutions can happen immediately after engaging with a problem, before participants explore all potential solutions. The conducted study exemplifies how ‘Dira’ can be used as an instrument to narrow down the moment when solutions emerge. We conclude that the ‘Dira’ experiment is paving the way to study the process, as opposed to the product, of creative problem solving. (shrink)

DOI: 10.1080/00031305.2018.1564697 When the editors of Basic and Applied Social Psychology effectively banned the use of null hypothesis significance testing (NHST) from articles published in their journal, it set off a fire-storm of discussions both supporting the decision and defending the utility of NHST in scientific research. At the heart of NHST is the p-value which is the probability of obtaining an effect equal to or more extreme than the one observed in the sample data, given the null hypothesis and (...) other model assumptions. Although this is conceptually different from the probability of the null hypothesis being true, given the sample, p-values nonetheless can provide evidential information, toward making an inference about a parameter. Applying a 10,000-case simulation described in this article, the authors found that p-values’ inferential signals to either reject or not reject a null hypothesis about the mean (α = 0.05) were consistent for almost 70% of the cases with the parameter’s true location for the sampled-from population. Success increases if a hybrid decision criterion, minimum effect size plus p-value (MESP), is used. Here, rejecting the null also requires the difference of the observed statistic from the exact null to be meaningfully large or practically significant, in the researcher’s judgment and experience. The simulation compares performances of several methods: from p-value and/or effect size-based, to confidence-interval based, under various conditions of true location of the mean, test power, and comparative sizes of the meaningful distance and population variability. For any inference procedure that outputs a binary indicator, like flagging whether a p-value is significant, the output of one single experiment is not sufficient evidence for a definitive conclusion. Yet, if a tool like MESP generates a relatively reliable signal and is used knowledgeably as part of a research process, it can provide useful information. (shrink)