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Recently I had the honor to be in a conversation about Bayesian hypothesis testing with the very well prepared Alex Andorra, for his popular podcast “Learning Bayesian Statistics”. If you want to check it out, please go to episode #61, “Why we still use non-Bayesian methods”.

Known as “the last universalist”, Henri Poincaré (1854-1912) made numerous contributions to mathematics and physics. He was also a philosopher of science who published three accessible and highly recommended books on science: “Science and Hypothesis”, “The Value of Science”, and “Science and Method” – this trilogy is now available as “The Foundations of Science”. In “Science and Method”, the chapter…

Many people believe that the future is partly in their own hands. We can usually choose freely whether to watch TV, or read a book, or go to the movies; we decide where to go on vacation, what to eat, whom to marry, and so on. There appears to be no external authority who commands us in such decisions, big…

This post is a teaser for Wagenmakers, E.-J. (2022). Approximate objective Bayes factors from p-values and sample size: The 3p√n rule. Preprint available on ArXiv: https://psyarxiv.com/egydq Abstract “In 1936, Sir Harold Jeffreys proposed an approximate objective Bayes factor that quantifies the degree to which the point-null hypothesis H0 outpredicts the alternative hypothesis H1. This approximate Bayes factor (henceforth JAB01) depends…

This post is an extended synopsis of two papers: The MARP Team (2022). A Many-Analysts Approach to the Relation Between Religiosity and Well-being. Preprint available on PsyArXiv: https://psyarxiv.com/pbfye/. Sarafoglou, Hoogeveen & Wagenmakers (2022). Comparing Analysis Blinding With Preregistration In The Many-Analysts Religion Project. Preprint available on PsyArXiv: https://psyarxiv.com/6dn8f/.  Summary The relation between religiosity and well-being is one of the most…

This post is a teaser for Wagenmakers, E.-J., & Ly, A. (2020). History and nature of the Jeffreys-Lindley paradox. Preprint available on ArXiv: https://arxiv.org/abs/2111.10191 Abstract “The Jeffreys-Lindley paradox exposes a rift between Bayesian and frequentist hypothesis testing that strikes at the heart of statistical inference. Contrary to what most current literature suggests, the paradox was central to the Bayesian testing…

This post is a synopsis of Bartoš, F., Maier, M., Quintana D. S., & Wagenmakers, E. (2021). Adjusting for Publication Bias in JASP & R — Selection Models, PET-PEESE, and Robust Bayesian Meta-Analysis. Preprint available at https://doi.org/10.31234/osf.io/kvsp7     Abstract Meta-analyses are essential for cumulative science, but their validity can be compromised by publication bias. In order to mitigate the…