Zobrazeno 1 - 10
of 390
pro vyhledávání: '"Bartoš, František"'
Autor:
Bartoš, František, Sarafoglou, Alexandra, Godmann, Henrik R., Sahrani, Amir, Leunk, David Klein, Gui, Pierre Y., Voss, David, Ullah, Kaleem, Zoubek, Malte J., Nippold, Franziska, Aust, Frederik, Vieira, Felipe F., Islam, Chris-Gabriel, Zoubek, Anton J., Shabani, Sara, Petter, Jonas, Roos, Ingeborg B., Finnemann, Adam, Lob, Aaron B., Hoffstadt, Madlen F., Nak, Jason, de Ron, Jill, Derks, Koen, Huth, Karoline, Terpstra, Sjoerd, Bastelica, Thomas, Matetovici, Magda, Ott, Vincent L., Zetea, Andreea S., Karnbach, Katharina, Donzallaz, Michelle C., John, Arne, Moore, Roy M., Assion, Franziska, van Bork, Riet, Leidinger, Theresa E., Zhao, Xiaochang, Motaghi, Adrian Karami, Pan, Ting, Armstrong, Hannah, Peng, Tianqi, Bialas, Mara, Pang, Joyce Y. -C., Fu, Bohan, Yang, Shujun, Lin, Xiaoyi, Sleiffer, Dana, Bognar, Miklos, Aczel, Balazs, Wagenmakers, Eric-Jan
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. In a preregistered study we collected $350{,}757$ coin flips to test the counterintuitive prediction from a physics model of human
Externí odkaz:
http://arxiv.org/abs/2310.04153
Autor:
Bartoš, František, Wagenmakers, Eric-Jan, Vinkers, Christiaan H., Braun, Kees P. J., Otte, Willem M.
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 developed a free, open, and user-friendly clinical trial aggregation pr
Externí odkaz:
http://arxiv.org/abs/2306.14061
Autor:
Bartoš, František, Otte, Willem M., Gronau, Quentin F., Timmers, Bram, Ly, Alexander, Wagenmakers, Eric-Jan
Bayesian model-averaged meta-analysis allows quantification of evidence for both treatment effectiveness $\mu$ and across-study heterogeneity $\tau$. We use the Cochrane Database of Systematic Reviews to develop discipline-wide empirical prior distri
Externí odkaz:
http://arxiv.org/abs/2306.11468
Autor:
Schimmack, Ulrich, Bartoš, František
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 examine the rate of false-positive results that have failed to settle thi
Externí odkaz:
http://arxiv.org/abs/2302.00774
Autor:
Bartoš, František, Maier, Maximilian, Wagenmakers, Eric-Jan, Nippold, Franziska, Doucouliagos, Hristos, Ioannidis, John P. A., Otte, Willem M., Sladekova, Martina, Deresssa, Teshome K., Bruns, Stephan B., Fanelli, Daniele, Stanley, T. D.
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 effect size estimates from medicine (67,386/597,699), environmental scien
Externí odkaz:
http://arxiv.org/abs/2208.12334
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 from multiple raters usually result in a binary outcome; the applicant
Externí odkaz:
http://arxiv.org/abs/2207.09101
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, or experience. Identification of such heterogeneity sources in IRR i
Externí odkaz:
http://arxiv.org/abs/2207.02071
Null hypothesis statistical significance testing (NHST) is the dominant approach for evaluating results from randomized controlled trials. Whereas NHST comes with long-run error rate guarantees, its main inferential tool -- the $p$-value -- is only a
Externí odkaz:
http://arxiv.org/abs/2206.04435
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 of Bayes factors can be challenging, however, and this has contributed
Externí odkaz:
http://arxiv.org/abs/2203.01435
Publikováno v:
BMC Med Res Methodol 22, 238 (2022)
We overview Bayesian estimation, hypothesis testing, and model-averaging and illustrate how they benefit parametric survival analysis. We contrast the Bayesian framework to the currently dominant frequentist approach and highlight advantages, such as
Externí odkaz:
http://arxiv.org/abs/2112.08311