55 citations · 266 across the 33 of their papers we have counts for
38 papers
Extracting Bayesian Evidence from Frequentist p-Values
Frederik Aust, Samuel Pawel, Eric-Jan Wagenmakers
The -value and the Bayes factor are measures of evidence that are often considered to be philosophically and mathematically incompatible: The -value quantifies conflict betwe…
Efficient Bayes Factor Sensitivity Analysis via Posterior Density Ratios
František Bartoš, Eric-Jan Wagenmakers, Maarten Marsman +1
Bayes factor sensitivity analysis examines how the evidence for one hypothesis over another depends on the prior distribution. In complex models, the standard approach refits the m…
Meta-Analysis with JASP, Part II: Bayesian Approaches
František Bartoš, Eric-Jan Wagenmakers
Bayesian inference is on the rise, partly because it allows researchers to quantify parameter uncertainty, evaluate evidence for competing hypotheses, incorporate model ambiguity,…
Meta-Analysis with JASP, Part I: Classical Approaches
František Bartoš, Eric-Jan Wagenmakers, Wolfgang Viechtbauer
Meta-analyses play a crucial part in empirical science, enabling researchers to synthesize evidence across studies and draw more precise and generalizable conclusions. Despite thei…
The Principle of Redundant Reflection
Martin Metodiev, Maarten Marsman, Lourens Waldorp +2
The fact that redundant information does not update a rational belief implies that rational beliefs are updated using Bayes rule. In the framework of Hild (1998a), this is true und…
Fair coins tend to land on the same side they started: Evidence from 350,757 flips
František Bartoš, Alexandra Sarafoglou, Henrik R. Godmann +47
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. We collected coin flips to test the counterintuit…
J. B. S. Haldane's Rule of Succession
Eric-Jan Wagenmakers, Sandy Zabell, Quentin F. Gronau
After Bayes, the oldest Bayesian account of enumerative induction is given by Laplace's so-called rule of succession: if all observed instances of a phenomenon to date exhibit…
Contextual aggregation and rapid updating of trial outcomes within a user-friendly open-source environment
František Bartoš, Eric-Jan Wagenmakers, Christiaan H. Vinkers +2
The delayed and incomplete availability of historical findings and the lack of integrative and user-friendly software hampers the reliable interpretation of new clinical data. We d…
Empirical prior distributions for Bayesian meta-analyses of binary and time to event outcomes
František Bartoš, Willem M. Otte, Quentin F. Gronau +3
Bayesian model-averaged meta-analysis allows quantification of evidence for both treatment effectiveness and across-study heterogeneity . We use the Cochrane Database of Sys…
Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics
František Bartoš, Maximilian Maier, Eric-Jan Wagenmakers +9
Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 eff…
Power priors for replication studies
Samuel Pawel, Frederik Aust, Leonhard Held +1
The ongoing replication crisis in science has increased interest in the methodology of replication studies. We propose a novel Bayesian analysis approach using power priors: The li…
When Evidence and Significance Collide
František Bartoš, Samuel Pawel, Eric-Jan Wagenmakers
Null hypothesis statistical significance testing (NHST) is the dominant approach for evaluating results from randomized controlled trials. Whereas NHST comes with long-run error ra…
Evidential Calibration of Confidence Intervals
Samuel Pawel, Alexander Ly, Eric-Jan Wagenmakers
We present a novel and easy-to-use method for calibrating error-rate based confidence intervals to evidence-based support intervals. Support intervals are obtained from inverting B…
Normalized power priors always discount historical data
Samuel Pawel, Frederik Aust, Leonhard Held +1
Power priors are used for incorporating historical data in Bayesian analyses by taking the likelihood of the historical data raised to the power as the prior distribution for t…
A general approximation to nested Bayes factors with informed priors
František Bartoš, Eric-Jan Wagenmakers
A staple of Bayesian model comparison and hypothesis testing, Bayes factors are often used to quantify the relative predictive performance of two rival hypotheses. The computation…
History and Nature of the Jeffreys-Lindley Paradox
Eric-Jan Wagenmakers, Alexander Ly
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 li…
Bayesian Model-Averaged Meta-Analysis in Medicine
František Bartoš, Quentin F. Gronau, Bram Timmers +3
We outline a Bayesian model-averaged meta-analysis for standardized mean differences in order to quantify evidence for both treatment effectiveness and across-study heterogenei…
A Puzzle of Proportions: Two Popular Bayesian Tests Can Yield Dramatically Different Conclusions
Fabian Dablander, Karoline Huth, Quentin F. Gronau +2
Testing the equality of two proportions is a common procedure in science, especially in medicine and public health. In these domains it is crucial to be able to quantify evidence f…
Bayes Factors for Peri-Null Hypotheses
Alexander Ly, Eric-Jan Wagenmakers
A perennial objection against Bayes factor point-null hypothesis tests is that the point-null hypothesis is known to be false from the outset. We examine the consequences of approx…
A Generalization of the Savage-Dickey Density Ratio for Testing Equality and Order Constrained Hypotheses
J. Mulder, E. -J. Wagenmakers, M. Marsman
The Savage-Dickey density ratio is a specific expression of the Bayes factor when testing a precise (equality constrained) hypothesis against an unrestricted alternative. The expre…
Default Bayes Factors for Testing the (In)equality of Several Population Variances
Fabian Dablander, Don van den Bergh, Eric-Jan Wagenmakers +1
Testing the (in)equality of variances is an important problem in many statistical applications. We develop default Bayes factor tests to assess the (in)equality of two or more popu…
BFpack: Flexible Bayes Factor Testing of Scientific Theories in R
Joris Mulder, Xin Gu, Anton Olsson-Collentine +10
There has been a tremendous methodological development of Bayes factors for hypothesis testing in the social and behavioral sciences, and related fields. This development is due to…
Many perspectives on Deborah Mayo's "Statistical Inference as Severe Testing: How to Get Beyond the Statistics Wars"
Andrew Gelman, Brian Haig, Christian Hennig +8
The new book by philosopher Deborah Mayo is relevant to data science for topical reasons, as she takes various controversial positions regarding hypothesis testing and statistical…
Informed Bayesian Inference for the A/B Test
Quentin F. Gronau, K. N. Akash Raj, Eric-Jan Wagenmakers
Booming in business and a staple analysis in medical trials, the A/B test assesses the effect of an intervention or treatment by comparing its success rate with that of a control c…