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…

## Adjusting for Publication Bias with JASP & R

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…

## Bayesian Model-Averaged Meta-Analysis in Medicine

This post is a synopsis of Bartoš, F., Gronau, Q. F., Timmers, B., Otte, W. M., Ly, A., & Wagenmakers, E. J. (2021). Bayesian model‐averaged meta‐analysis in medicine. Statistics in Medicine. The article is available at https://doi.org/10.1002/sim.9170  (open-access).   Abstract We outline a Bayesian model-averaged (BMA) meta-analysis for standardized mean differences in order to quantify evidence for both treatment effectiveness…

## Literal and Liberal Translations of Bertrand’s Box Paradox

In his 1889 book “Calcul des Probabilités”, the French mathematician Joseph Bertrand (1822–1900) introduced a probability paradox that anticipates both the Monty Hall problem and the Three Prisoners problem. Below we first present a literal translation of Bertrand’s text, which unfortunately suffers from being somewhat unclear. We therefore follow it up with a more liberal translation, and end with a…

## Preprint: Computing and Using Inclusion Bayes Factors for Mixed Fixed and Random Effect Diffusion Decision Models

This post is a synopsis of Boehm U, Evans N J, Gronau D., Matzke D, Wagenmakers E.-J., & Heathcote A J. (2021). Computing and using inclusion Bayes factors for mixed fixed and random effect diffusion decision models. Preprint available at https://psyarxiv.com/45t2w Abstract Cognitive models provide a substantively meaningful quantitative description of latent cognitive processes. The quantitative formulation of these models…

## Preprint: No Need to Choose: Robust Bayesian Meta-Analysis With Competing Publication Bias Adjustment Methods

This post is a synopsis of Bartoš, F, Maximilian M, Wagenmakers E.-J., Doucouliagos H., & Stanley, T D. (2021). No need to choose: Robust Bayesian meta-analysis with competing publication bias adjustment methods. Preprint available at https://doi.org/10.31234/osf.io/kvsp7 Abstract “Publication bias is a ubiquitous threat to the validity of meta-analysis and the accumulation of scientific evidence. In order to estimate and counteract…