Why we should replace power analyses and significance testing with the a priori procedure and gain-probability analyses

We are pleased to welcome Prof. David Trafimow, professor of psychological methods at New Mexico State University, who will be visiting us in Munich.
The talk will also be broadcast via Zoom and is open to everyone who is interested: https://lmu-munich.zoom-x.de/j/219348271?pwd=ZkYyT0JrbHBFS1FreFNYMENFU05jdz09
(Meeting ID: 219 348 271; Passcode: 647311)

The standard statistical procedure for researchers comprises a two-step process. Before data collection, researchers perform power analyses, and after data collection, they perform significance tests. There is a much better post-data option that provides a higher grade of useful information. It is possible to estimate probabilities of being better off or worse off, by varying degrees, depending on whether one gets the treatment or not. In turn, if the post-data goal switches from significance testing to a concern with probabilistic advantages or disadvantages, an implication is that the pre-data goal ought to switch accordingly. The a priori procedure, with its focus on parameter estimation, should replace conventional power analysis as a pre-data procedure. Therefore, the new two-step procedure should be the a priori procedure pre-data and estimations of probabilities of being better off, or worse off, to varying degrees, post-data.

About Prof. David Trafimow

David Trafimow is known for his work on statistical methods in psychology. As editor-in-chief of the journal Basic and Applied Social Psychology, he initiated the journal's ban on reporting null-hypothesis significance tests in 2014. A selection of his recent publications:

• Trafimow, D. (2026). Binomial effect size displays and gain-probability: Alternative ways to interpret hierarchical regression findings, with tutorial. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000839

• Trafimow, D., & Fiedler, K. (2026). An exploration of physics envy with implications for desiderata of psychology theories. American Psychologist, 81(1), 94–108. https://doi.org/10.1037/amp0001416

• Trafimow, D., Hyman, M. R., & Kostyk, A. (2025). Enhancing predictive power by unamalgamating multi-item scales. Psychological Methods, 30(5), 1043–1055. https://doi.org/10.1037/met0000599