5 citations · 8 across the 7 of their papers we have counts for
7 papers
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…
Single-Dataset Meta-Analysis For Many-Analysts And Multiverse Studies
František Bartoš, Suzanne Hoogeveen, Alexandra Sarafoglou +1
Empirical claims often rely on one population, design, and analysis. Many-analysts, multiverse, and robustness studies expose how results can vary across plausible analytic choices…
Living Synthetic Benchmarks: A Neutral and Cumulative Framework for Simulation Studies
František Bartoš, Samuel Pawel, Björn S. Siepe
Simulation studies are widely used to evaluate statistical methods. However, new methods are often introduced and evaluated using data-generating mechanisms (DGMs) devised by the s…
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,…
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…
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…