Quantifying Support for the Null Hypothesis in Psychology: An Empirical Investigation

This post summarizes the content of an article that is in press for Advances in Methods and Practices in Psychological Science.1 The preprint is available on PsyArXiv. In the traditional statistical framework, nonsignificant results leave researchers in a state of suspended disbelief. This study examines, empirically, the treatment and evidential impact of nonsignificant results. Our specific goals were twofold: to…

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Bayesian Reanalysis of Null Results Reported in Medicine: Strong Yet Variable Evidence for the Absence of Treatment Effects

This post summarizes the content of an article that is in press for PLOS ONE. The preprint is available on PsyArXiv. Efficient medical progress requires that we know when a treatment effect is absent. We considered all 207 Original Articles published in the 2015 volume of the New England Journal of Medicine and found that 45 (21.7%) reported a null…

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Bayesian Tutorials Galore

This post highlights a recent special issue on Bayesian inference edited by Joachim Vandekerckhove, Jeff Rouder, and John Kruschke for Psychonomic Bulletin & Review. What sets this special issue apart is that most of the 16 contributions (spanning a total of 285 pages!) have a tutorial character. Researchers and students who are new to Bayesian inference –its theoretical underpinnings, its…

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The Creativity-Verification Cycle in Psychological Science: New Methods to Combat Old Idols, Part I

The promised post on Einstein will follow next week. More and more psychologists are registering their hypotheses, predictions, and analysis plans prior to data collection. Will such preregistration be the death knell for creativity and serendipity? Gilles Dutilh, Alexandra Sarafoglou, and I recently wrote an article for Perspectives on Psychological Science that provides a historical perspective on this question. In…

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Redefine Statistical Significance Part XV: Do 72+88=160 Researchers Agree on P?

In an earlier blog post we discussed a response (co-authored by 88 researchers) to the paper “Redefine Statistical Significance” (RSS; co-authored by 72 researchers). Recall that RSS argued that p-values near .05 should be interpreted with caution, and proposed that a threshold of .005 is more in line with the kind of evidence that warrants strong claims such as “reject…

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The Case for Radical Transparency in Statistical Reporting

Today I am giving a lecture at the Replication and Reproducibility Event II: Moving Psychological Science Forward, organised by the British Psychological Society. The lecture is similar to the one I gave a few months ago at an ASA meeting in Bethesda, and it makes the case for radical transparency in statistical reporting. The talking points, in order: The researcher…

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