We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries. T he lack of reproducibility of scientific studies has caused growing concern over the credibility of claims of new discoveries based on 'statistically significant' findings. There has been much progress toward documenting and addressing several causes of this lack of reproducibility (for example, multiple testing, P-hacking, publication bias and under-powered studies). However, we believe that a leading cause of non-reproducibility has not yet been adequately addressed: statistical standards of evidence for claiming new discoveries in many fields of science are simply too low. Associating statistically significant findings with P < 0.05 results in a high rate of false positives even in the absence of other experimental, procedural and reporting problems.For fields where the threshold for defining statistical significance for new discoveries is P < 0.05, we propose a change to P < 0.005. This simple step would immediately improve the reproducibility of scientific research in many fields. Results that would currently be called significant but do not meet the new threshold should instead be called suggestive. While statisticians have known the relative weakness of using P ≈ 0.05 as a threshold for discovery and the proposal to lower it to 0.005 is not new 1,2 , a critical mass of researchers now endorse this change.We restrict our recommendation to claims of discovery of new effects. We do not address the appropriate threshold for confirmatory or contradictory replications of existing claims. We also do not advocate changes to discovery thresholds in fields that have already adopted more stringent standards (for example, genomics and high-energy physics research; see the 'Potential objections' section below).We also restrict our recommendation to studies that conduct null hypothesis significance tests. We have diverse views about how best to improve reproducibility, and many of us believe that other ways of summarizing the data, such as Bayes factors or other posterior summaries based on clearly articulated model assumptions, are preferable to P values. However, changing the P value threshold is simple, aligns with the training undertaken by many researchers, and might quickly achieve broad acceptance.

In an attempt to eliminate similar item content as an alternative explanation for the relation between depression and rumination, a secondary analysis was conducted using the data from S. Nolen-Hoeksema, J. Larson, and C. Grayson (1999). After constructing a measure of rumination unconfounded with depression content, support for a two factor model of rumination was found. These analyses indicate that the 2 components, reflective pondering and brooding, differentially relate to depression in terms of predictive ability and gender difference mediation. The results presented here support the general premise of Nolen-Hoeksema's Response Styles Theory (S. Nolen-Hoeksema 1987) that rumination can contribute to more depressive symptoms and to the gender difference in depression, but suggest important refinements of the theory. Such refinements include the need to differentiate between the reflective pondering component of rumination and the brooding component in rumination research.

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When individuals choose among risky alternatives, the psychological weight attached to an outcome may not correspond to the probability of that outcome. In rank-dependent utility theories, including prospect theory, the probability weighting function permits probabilities to be weighted nonlinearly. Previous empirical studies of the weighting function have suggested an inverse S-shaped function, first concave and then convex. However, these studies suffer from a methodological shortcoming: estimation procedures have required assumptions about the functional form of the value and/or weighting functions. We propose two preference conditions that are necessary and sufficient for concavity and convexity of the weighting function. Empirical tests of these conditions are independent of the form of the value function. We test these conditions using preference "ladders" (a series of questions that differ only by a common consequence). The concavity-convexity ladders validate previous findings of an S-shaped weighting function, concave up to pdecision making, expected utility, nonexpected utility theory, prospect theory, risk, risk aversion

We show that differences in social orientation and in cognition that exist between cultures and social classes do not necessarily have counterparts in individual differences within those groups. Evidence comes from a large-scale study conducted with 10 measures of independent vs. interdependent social orientation and 10 measures of analytic vs. holistic cognitive style. The social measures successfully distinguish between interdependence (viewing oneself as embedded in relations with others) and independence (viewing oneself as disconnected from others) at the group level. However, the correlations among the measures were negligible. Similar results were obtained for the cognitive measures, for which there are no coherent individual differences despite the validity of the construct at the group level. We conclude that behavioral constructs that distinguish among groups need not be valid as measures of individual differences.