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20212026
most citedBayesian Model-Averaged Meta-Analysis in Medicine

55 citations · 150 across the 12 of their papers we have counts for

collaborators

12 papers

stat.ME2026

Why the unrestricted weighted least squares should be routinely reported in medical meta-analyses

T. D. Stanley, John P. A. Ioannidis, Maximilian Maier +3

The unrestricted weighted least squares (UWLS) meta-analysis estimator of mean effect is an alternative to the conventional random-effects model (RE). It is a weighted least square…

stat.ME2025

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…

stat.ME2025

Z-Curve Plot: A Visual Diagnostic for Publication Bias in Meta-Analysis

František Bartoš, Ulrich Schimmack

Publication bias undermines meta-analytic inference, yet visual diagnostics for detecting and understanding model misfit due to publication bias are lacking. We propose the z-plot,…

stat.ME2024

Handling Missingness, Failures, and Non-Convergence in Simulation Studies: A Review of Current Practices and Recommendations

Samuel Pawel, František Bartoš, Björn S. Siepe +1

Simulation studies are commonly used in methodological research for the empirical evaluation of data analysis methods. They generate artificial data sets under specified mechanisms…

math.HO2023★ 7 cited

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…

stat.AP2023★ 10 cited

Estimating the false discovery risk of (randomized) clinical trials in medical journals based on published p-values

Ulrich Schimmack, František Bartoš

The influential claim that most published results are false raised concerns about the trustworthiness and integrity of science. Since then, there have been numerous attempts to exa…

stat.AP2022★ 55 cited

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…

stat.ME2022★ 2 cited

Assessing quality of selection procedures: Lower bound of false positive rate as a function of inter-rater reliability

František Bartoš, Patrícia Martinková

Inter-rater reliability (IRR) is one of the commonly used tools for assessing the quality of ratings from multiple raters. However, applicant selection procedures based on ratings…

stat.ME2022★ 9 cited

Assessing inter-rater reliability with heterogeneous variance components models: Flexible approach accounting for contextual variables

Patrícia Martinková, František Bartoš, Marek Brabec

Inter-rater reliability (IRR), which is a prerequisite of high-quality ratings and assessments, may be affected by contextual variables such as the rater's or ratee's gender, major…

stat.ME2022★ 9 cited

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…

stat.ME2021★ 3 cited

Informed Bayesian survival analysis

František Bartoš, Frederik Aust, Julia M. Haaf

We overview Bayesian estimation, hypothesis testing, and model-averaging and illustrate how they benefit parametric survival analysis. We contrast the Bayesian framework to the cur…

stat.ME2021★ 55 cited

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…