This post is an extended synopsis of Ly et al. (2019). The Bayesian methodology of Sir Harold Jeffreys as a practical alternative to the p-value hypothesis test. Preprint available on PsyArXiv: https://psyarxiv.com/dhb7x

Abstract

Despite an ongoing stream of lamentations, many empirical disciplines still treat the p-value as the sole arbiter to separate the scientific wheat from the chaff. The continued reign of the p-value is arguably due in part to a perceived lack of workable alternatives. In order to be workable, any alternative methodology must be (1) relevant: it has to address the practitioners’ research question, which –for better or for worse– most often concerns the test of a hypothesis, and less often concerns the estimation of a parameter; (2) available: it must have a concrete implementation for practitioners’ statistical workhorses such as the t-test, regression, and ANOVA; and (3) easy to use: methods that demand practitioners switch to the theoreticians’ programming tools will face an uphill struggle for adoption. The above desiderata are fulfilled by Harold Jeffreys’s Bayes factor methodology as implemented in the open-source software JASP. We explain Jeffreys’s methodology and showcase its practical relevance with two examples.

Default Bayesian Reanalysis of Strack et al.’s Facial Feedback Experiment

Informed Bayesian Analysis of a Facial Feedback Replication Attempt

Linear Regression

References

Ly, A., Stefan, A., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., Kucharsky, S., Derks, K., Gronau, Q. F., Raj, A., Boehm, U., van Kesteren, E.-J., Hinne, M., Matzke, D., Marsman, M., & Wagenmakers, E.-J. (2019). The Bayesian methodology of Sir Harold Jeffreys as a practical alternative to the p-value hypothesis test. Manuscript submitted for publication. PsyArXiv: https://psyarxiv.com/dhb7x

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