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Ruud Wetzels
Researcher at University of Amsterdam
Publications - 35
Citations - 3978
Ruud Wetzels is an academic researcher from University of Amsterdam. The author has contributed to research in topics: Bayes factor & Iowa gambling task. The author has an hindex of 20, co-authored 35 publications receiving 3401 citations. Previous affiliations of Ruud Wetzels include PricewaterhouseCoopers & European Foundation for the Improvement of Living and Working Conditions.
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An agenda for purely confirmatory research
TL;DR: This article proposes that researchers preregister their studies and indicate in advance the analyses they intend to conduct, and proposes that only these analyses deserve the label “confirmatory,” and only for these analyses are the common statistical tests valid.
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Why psychologists must change the way they analyze their data: the case of psi: comment on Bem (2011).
TL;DR: It is concluded that Bem's p values do not indicate evidence in favor of precognition; instead, they indicate that experimental psychologists need to change the way they conduct their experiments and analyze their data.
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Statistical Evidence in Experimental Psychology An Empirical Comparison Using 855 t Tests
Ruud Wetzels,Dora Matzke,Michael D. Lee,Jeffrey N. Rouder,Geoffrey J. Iverson,Eric-Jan Wagenmakers +5 more
TL;DR: The authors provide a practical comparison of p values, effect sizes, and default Bayes factors as measures of statistical evidence, using 855 recently published t tests in psychology and conclude that the Bayesian approach is comparatively prudent, preventing researchers from overestimating the evidence in favor of an effect.
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A default Bayesian hypothesis test for correlations and partial correlations
TL;DR: A default Bayesian hypothesis test for the presence of a correlation or a partial correlation is proposed, which can quantify evidence in favor of the null hypothesis and allows researchers to monitor the test results as the data come in.
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Hidden multiplicity in exploratory multiway ANOVA: Prevalence and remedies.
Angélique O. J. Cramer,Don van Ravenzwaaij,Dora Matzke,Helen Steingroever,Ruud Wetzels,Raoul P. P. P. Grasman,Lourens J. Waldorp,Eric-Jan Wagenmakers +7 more
TL;DR: This work explains the multiple-comparison problem and demonstrates that researchers almost never correct for it, and describes four remedies: the omnibus F test, control of the familywise error rate, controls of the false discovery rate, and preregistration of the hypotheses.