Prof. dr. E.M. (Eric-Jan) Wagenmakers

Faculty of Social and Behavioural Sciences

Programme group Psychological Methods

Photographer: UvA Persvoorlichting

Visiting address

Nieuwe Achtergracht 129
Room number: 0.29

Postal address

Postbus 15906
1001 NK Amsterdam

Contact details

Social media

Profile
Prof. dr. Eric-Jan Wagenmakers is a mathematical psychologist and a dedicated Bayesian. His lab heads the development of the JASP open-source software program for statistical analyses. Prof. Wagenmakers is a strong advocate of Open Science and the preregistration of analysis plans. He has also authored the book "Bayesian Thinking for Toddlers", which is a must-have for any toddler with even a passing interest in Ockham’s razor and the prequential principle.

Expertise and research fields

Bayesian inference

Cognitive modeling

Philosophy of science

Teaching in statistics
Research

Please follow this link for a full overview of all papers published by professor Wagenmakers.
Teaching & PhD Supervision
Good Research Practices (with Dora Matzke)

Bayesian Inference for Psychological Science (with Dora Matzke)

Bayesian Hypothesis Testing in Practice

Behavioural Data Science (with Denny Borsboom)
Publications
2024

Hoogeveen, S., Borsboom, D., Kucharský, Š., Marsman, M., Molenaar, D., de Ron, J., Sekulovski, N., Visser, I., van Elk, M., & Wagenmakers, E.-J. (2024). Prevalence, patterns and predictors of paranormal beliefs in The Netherlands: a several-analysts approach. Royal Society Open Science, 11(9), Article 240049. https://doi.org/10.1098/rsos.240049 [details]
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Sekulovski, N., Keetelaar, S., Huth, K., Wagenmakers, E. J., van Bork, R., van den Bergh, D., & Marsman, M. (2024). Testing Conditional Independence in Psychometric Networks: An Analysis of Three Bayesian Methods. Multivariate Behavioral Research, 59(5), 913-933. https://doi.org/10.1080/00273171.2024.2345915

Sekulovski, N., Marsman, M., & Wagenmakers, E. J. (2024). A Good check on the Bayes factor. Behavior Research Methods, 56(8), 8552–8566. Advance online publication. https://doi.org/10.3758/s13428-024-02491-4

2023

Bartoš, F., & Wagenmakers, E.-J. (2023). A general approximation to nested Bayes factors with informed priors. Stat, 12(1), Article e600. https://doi.org/10.1002/sta4.600 [details]
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Bartoš, F., Maier, M., Shanks, D. R., Stanley, T. D., Sladekova, M., & Wagenmakers, E.-J. (2023). Meta-analyses in psychology often overestimate evidence for and size of effects. Royal Society Open Science, 10(7), Article 230224. https://doi.org/10.1098/rsos.230224 [details]
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Bartoš, F., Maier, M., Wagenmakers, E.-J., Doucouliagos, H., & Stanley, T. D. (2023). Robust Bayesian meta-analysis: Model-averaging across complementary publication bias adjustment methods. Research synthesis methods, 14(1), 99-116. https://doi.org/10.1002/jrsm.1594 [details]
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Research Synthesis Methods - 2022 - Barto - Robust Bayesian meta‐analysis Model‐averaging across complementary publication
Supplementary files
jrsm1594-sup-0001-appendix

Berkhout, S. W., Haaf, J. M., Gronau, Q. F., Heck, D. W., & Wagenmakers, E. J. (2023). A tutorial on Bayesian model-averaged meta-analysis in JASP. Behavior Research Methods. Advance online publication. https://doi.org/10.3758/s13428-023-02093-6

Boehm, U., Evans, N. J., Gronau, Q. F., Matzke, D., Wagenmakers, E. J., & Heathcote, A. J. (2023). Inclusion Bayes Factors for Mixed Hierarchical Diffusion Decision Models. Psychological Methods. Advance online publication. https://doi.org/10.31234/osf.io/45t2w, https://doi.org/10.1037/met0000582

Dablander, F., van den Bergh, D., Ly, A., & Wagenmakers, E. M. (2023). Default Bayes Factors for Testing the (In)equality of Several Population Variances. Bayesian Analysis. Advance online publication. https://doi.org/10.48550/arXiv.2003.06278, https://doi.org/10.1214/23-BA1369

Hardwicke, T. E., & Wagenmakers, E.-J. (2023). Reducing bias, increasing transparency and calibrating confidence with preregistration. Nature Human Behaviour, 7, 15-26. https://doi.org/10.1038/s41562-022-01497-2 [details]
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s41562-022-01497-2
Supplementary files
41562 2022 1497 MOESM1 ESM

Hoogeveen, S., Berkhout, S. W., Gronau, Q. F., Wagenmakers, E.-J., & Haaf, J. M. (2023). Improving Statistical Analysis in Team Science: The Case of a Bayesian Multiverse of Many Labs 4. Advances in Methods and Practices in Psychological Science, 6(3). https://doi.org/10.1177/25152459231182318 [details]
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Hoogeveen, S., Sarafoglou, A., Bartoš, F., Beitner, J., De Ron, J., Gligoric, V., Kleinberg, B., Van der Cruyssen, I., van Dongen, N. N. N., van Ravenzwaaij, D., Verschuere, B., Wiechert, S., Zarzeczna, N., van Elk, M., Wagenmakers, E.-J., Većkalov, B., & The MARP Team (2023). A many-analysts approach to the relation between religiosity and well-being. Religion, Brain & Behavior, 13(3), 237-283. https://doi.org/10.1080/2153599X.2022.2070255 [details]
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A many-analysts approach to the relation between religiosity and well-being
Supplementary files
rrbb a 2070255 sm1589

Hoogeveen, S., Sarafoglou, A., van Elk, M., & Wagenmakers, E.-J. (2023). Introducing the Many-Analysts Religion Project. Religion, Brain and Behavior, 13(3), 233-236. https://doi.org/10.1080/2153599X.2023.2254980 [details]

Hoogeveen, S., van Elk, M., & Wagenmakers, E. M. (2023). Geloof in het bovennatuurlijke daalt fors. Skepter, 36, 5-13.

Huth, K. B. S., de Ron, J., Goudriaan, A. E., Luigjes, J., Mohammadi, R., van Holst, R. J., Wagenmakers, E.-J., & Marsman, M. (2023). Bayesian Analysis of Cross-Sectional Networks: A Tutorial in R and JASP. Advances in Methods and Practices in Psychological Science, 6(4), 1-18. https://doi.org/10.1177/25152459231193334 [details]
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Maier, M., Bartoš, F., & Wagenmakers, E.-J. (2023). Robust Bayesian meta-analysis: Addressing publication bias with model-averaging. Psychological Methods, 28(1), 107-122. https://doi.org/10.1037/met0000405 [details]

Pawel, S., Aust, F., Held, L., & Wagenmakers, E.-J. (2023). Normalized power priors always discount historical data. Stat, 12(1), Article e591. https://doi.org/10.1002/sta4.591 [details]
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Sarafoglou, A., Aust, F., Marsman, M., Bartoš, F., Wagenmakers, E.-J., & Haaf, J. M. (2023). Multibridge: an R package to evaluate informed hypotheses in binomial and multinomial models. Behavior Research Methods, 55(8), 4343-4368. https://doi.org/10.3758/s13428-022-02020-1 [details]
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Sarafoglou, A., Bartoš, F., Stefan, A., Haaf, J. M., & Wagenmakers, E. J. (2023). “This behavior strikes us as ideal”: assessment and anticipations of Huisman (2022). Psychonomic Bulletin and Review. Advance online publication. https://doi.org/10.3758/s13423-023-02299-x

Sarafoglou, A., Haaf, J. M., Ly, A., Gronau, Q. F., Wagenmakers, E.-J., & Marsman, M. (2023). Evaluating Multinomial Order Restrictions With Bridge Sampling. Psychological Methods, 28(2), 322-338. https://doi.org/10.1037/met0000411 [details]
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Sarafoglou, A., Hoogeveen, S., & Wagenmakers, E.-J. (2023). Comparing Analysis Blinding With Preregistration in the Many-Analysts Religion Project. Advances in Methods and Practices in Psychological Science, 6(1). https://doi.org/10.1177/25152459221128319 [details]
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Visser, I., Kucharský, Š., Levelt, C., Stefan, A. M., Wagenmakers, E. J., & Oakes, L. (2023). Bayesian sample size planning for developmental studies. Infant and Child Development, Article e2412. Advance online publication. https://doi.org/10.1002/icd.2412

Wagenmakers, E. M. (2023). De psi van sex. Skepter, 36, 37-38.

Wagenmakers, E. M., Zabell, S., & Gronau, Q. F. (2023). J. B. S. Haldane's Rule of Succession. Statistical Science, 1-14. https://doi.org/10.48550/arXiv.2307.09489

Wagenmakers, E. M., van Doorn, J. B., & van den Bergh, D. (2023). Toegankelijke en duurzame statistiek met JASP. STAtOR, 24, 41-47.

Wagenmakers, E.-J., & Ly, A. (2023). History and nature of the Jeffreys–Lindley paradox. Archive for History of Exact Sciences, 77(1), 25-72. https://doi.org/10.1007/s00407-022-00298-3 [details]
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Wagenmakers, E.-J., Sarafoglou, A., & Aczel, B. (2023). Facing the Unknown Unknowns of Data Analysis. Current Directions in Psychological Science, 32(5), 362-368. https://doi.org/10.1177/09637214231168565 [details]
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Wang, Y., van den Bergh, D., Aust, F., Ly, A., Wagenmakers, E. M., & Hu, C. (2023). The implementation of Bayesian ANOVA in JASP: A Practical Primer. Psychology: Techniques and Application, 11(9), 528-541.

van Dongen, N., Sprenger, J., & Wagenmakers, E.-J. (2023). A Bayesian perspective on severity: risky predictions and specific hypotheses. Psychonomic Bulletin and Review, 30(2), 516–533. https://doi.org/10.3758/s13423-022-02069-1 [details]
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van Doorn, J., Aust, F., Haaf, J. M., Stefan, A. M., & Wagenmakers, E.-J. (2023). Bayes Factors for Mixed Models. Computational Brain and Behavior, 6(1), 1–13. https://doi.org/10.1007/s42113-021-00113-2 [details]
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s42113-021-00113-2
Supplementary files
42113 2021 113 MOESM1 ESM

van Ravenzwaaij, D., Bakker, M., Heesen, R., Romero, F., van Dongen, N., Crüwell, S., Field, S. M., Held, L., Munafò, M. R., Pittelkow, M. M., Tiokhin, L., Traag, V. A., van den Akker, O. R., van 't Veer, A. E., & Wagenmakers, E. J. (2023). Perspectives on Scientific Error. Royal Society Open Science, 10(7), Article 230448. https://doi.org/10.31234/osf.io/wm4v6, https://doi.org/10.1098/rsos.230448 [details]
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van den Bergh, D., Schuringa, E., & Wagenmakers, E. M. (2023). Augmenting Predictive Models in Forensic Psychiatry with Cultural Consensus Theory. Journal of the Royal Statistical Society. Series C: Applied Statistics, 1-16. https://doi.org/10.31234/osf.io/9kp3y

van den Bergh, D., Wagenmakers, E.-J., & Aust, F. (2023). Bayesian Repeated-Measures Analysis of Variance: An Updated Methodology Implemented in JASP. Advances in Methods and Practices in Psychological Science, 6(2). https://doi.org/10.1177/25152459231168024 [details]
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2022

Bartoš, F., Maier, M., Quintana, D. S., & Wagenmakers, E.-J. (2022). Adjusting for Publication Bias in JASP and R: Selection Models, PET-PEESE, and Robust Bayesian Meta-Analysis. Advances in Methods and Practices in Psychological Science, 5(3). https://doi.org/10.31234/osf.io/75bqn, https://doi.org/10.1177/25152459221109259 [details]
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Bartoš, F., Maier, M., Wagenmakers, E. M., Nippold, F., Doucouliagos, H., Ioannidis, J. P. A., Otte, W. M., Martina, S., Fanelli, D., & Stanley, T. D. (2022). Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics. Research synthesis methods, 1-19. https://doi.org/10.48550/arXiv.2208.12334

Dablander, F., Huth, K., Gronau, Q. F., Etz, A., & Wagenmakers, E-J. (2022). A puzzle of proportions: Two popular Bayesian tests can yield dramatically different conclusions. Statistics in Medicine, 41(8), 1319-1333. Advance online publication. https://doi.org/10.1002/sim.9278 [details]
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Forscher, P. S., Wagenmakers, E. J., Coles, N. A., Silan, M. A., Dutra, N., Basnight-Brown, D., & IJzerman, H. (2022). The Benefits, Barriers, and Risks of Big-Team Science. Perspectives on Psychological Science. Advance online publication. https://doi.org/10.1177/17456916221082970

Hoffmann, T., Hofman, A., & Wagenmakers, E.-J. (2022). Bayesian Tests of Two Proportions: A Tutorial With R and JASP. Methodology, 18(4), 239-277. https://doi.org/10.5964/meth.9263 [details]
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Hoogeveen, S., Sarafoglou, A., van Elk, M., & Wagenmakers, E. J. (2022). Many-analysts religion project:reflection and conclusion. Religion, Brain and Behavior. Advance online publication. https://doi.org/10.1080/2153599X.2022.2070263

Linde, M., Tendeiro, J. N., Wagenmakers, E. M., & van Ravenzwaaij, D. (2022). Practical Implications of Equating Equivalence Tests: Reply to Campbell and Gustafson (2022). Psychological Methods, 1-11. https://doi.org/10.31234/osf.io/xk43y

Ly, A., & Wagenmakers, E.-J. (2022). A Critical Evaluation of the FBST ev for Bayesian Hypothesis Testing. Computational Brain and Behavior, 5(4), 564-571. https://doi.org/10.31234/osf.io/x9t6n, https://doi.org/10.1007/s42113-021-00109-y [details]
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Ly, A., & Wagenmakers, E.-J. (2022). Bayes factors for peri-null hypotheses. Test, 31(4), 1121-1142. https://doi.org/10.1007/s11749-022-00819-w [details]
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Ly, A., & Wagenmakers, E.-J. (2022). Measure-Theoretic Musings Cannot Salvage the Full Bayesian Significance Test as a Measure of Evidence. Computational Brain and Behavior, 5(4), 583-289. https://doi.org/10.1007/s42113-022-00154-1 [details]
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Manning, C., Hassall, C. D., Hunt, L. T., Norcia, A. M., Wagenmakers, E-J., Evans, N. J., & Scerif, G. (2022). Behavioural and neural indices of perceptual decision-making in autistic children during visual motion tasks. Scientific Reports, 12, Article 6072. https://doi.org/10.1038/s41598-022-09885-4 [details]
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s41598-022-09885-4
Supplementary files
41598 2022 9885 MOESM1 ESM

Manning, C., Hassall, C. D., Hunt, L. T., Norcia, A. M., Wagenmakers, E-J., Snowling, M. J., Scerif, G., & Evans, N. J. (2022). Visual Motion and Decision-Making in Dyslexia: Reduced Accumulation of Sensory Evidence and Related Neural Dynamics. The Journal of Neuroscience, 42(1), 121-134. https://doi.org/10.1523/JNEUROSCI.1232-21.2021 [details]
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Mulder, J., Wagenmakers, E.-J., & Marsman, M. (2022). A Generalization of the Savage–Dickey Density Ratio for Testing Equality and Order Constrained Hypotheses. American Statistician, 76(2), 102-109. https://doi.org/10.1080/00031305.2020.1799861 [details]
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Pawel, S., Aust, F., Held, L., & Wagenmakers, E. M. (2022). Power priors for replication studies. Test. https://doi.org/10.48550/arXiv.2207.14720

Pfadt, J. M., Bergh, D. V. D., Sijtsma, K., & Wagenmakers, E. J. (2022). A tutorial on Bayesian single-test reliability analysis with JASP. Behavior Research Methods. Advance online publication. https://doi.org/10.3758/s13428-021-01778-0

Pfadt, J. M., van den Bergh, D., Sijtsma, K., Moshagen, M., & Wagenmakers, E.-J. (2022). Bayesian Estimation of Single-Test Reliability Coefficients. Multivariate Behavioral Research, 57(4), 620-641. https://doi.org/10.1080/00273171.2021.1891855 [details]
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Rosenberg, J. M., Kubsch, M., Wagenmakers, E.-J., & Dogucu, M. (2022). Making Sense of Uncertainty in the Science Classroom: A Bayesian Approach. Science and Education, 31(5), 1239-1262. https://doi.org/10.1007/s11191-022-00341-3 [details]
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s11191-022-00341-3
Supplementary files
11191 2022 341 MOESM1 ESM

Sarafoglou, A., Kovacs, M., Bakos, B., Wagenmakers, E.-J., & Aczel, B. (2022). A survey on how preregistration affects the research workflow: better science but more work. Royal Society Open Science, 9(7), Article 211997. https://doi.org/10.1098/rsos.211997 [details]
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Sarafoglou, A., van der Heijden, A., Draws, T., Cornelisse, J., Wagenmakers, E.-J., & Marsman, M. (2022). Combine Statistical Thinking With Open Scientific Practice: A Protocol of a Bayesian Research Project. Psychology Learning and Teaching, 21(2), 138-150. https://doi.org/10.1177/14757257221077307 [details]
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14757257221077307
Supplementary files
sj-docx-1-plj-10.1177 14757257221077307

Stefan, A. M., Evans, N. J., & Wagenmakers, E-J. (2022). Practical Challenges and Methodological Flexibility in Prior Elicitation. Psychological Methods, 27(2), 177-197. Advance online publication. https://doi.org/10.31234/osf.io/d42xb, https://doi.org/10.1037/met0000354 [details]

Stefan, A. M., Gronau, Q. F., & Wagenmakers, E. M. (2022). Interim Design Analysis Using Bayes Factor Forecasts. Psychological Methods, 1-50. https://doi.org/10.31234/osf.io/9sazk

Stefan, A. M., Katsimpokis, D., Gronau, Q. F., & Wagenmakers, E-J. (2022). Expert agreement in prior elicitation and its effects on Bayesian inference. Psychonomic Bulletin and Review, 29(5), 1776-1794. Advance online publication. https://doi.org/10.3758/s13423-022-02074-4 [details]
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Stefan, A. M., Lengersdorff, L. L., & Wagenmakers, E-J. (2022). A Two-Stage Bayesian Sequential Assessment of Exploratory Hypotheses. Collabra: Psychology, 8, Article 40350. Advance online publication. https://doi.org/10.1525/collabra.40350 [details]
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collabra 2022 8 1 40350
Supplementary files
collabra 2022 8 1 40350 104198
collabra 2022 8 1 40350 104199

Stefan, A. M., Schönbrodt, F. D., Evans, N. J., & Wagenmakers, E.-J. (2022). Efficiency in sequential testing: Comparing the sequential probability ratio test and the sequential Bayes factor test. Behavior Research Methods, 54(6), 3100-3117. https://doi.org/10.31234/osf.io/ry4fw, https://doi.org/10.3758/s13428-021-01754-8 [details]
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Temp, A. G. M., Ly, A., van Doorn, J., Wagenmakers, E.-J., Tang, Y., Lutz, M. W., & Teipel, S. (2022). A Bayesian perspective on Biogen's aducanumab trial. Alzheimer's and Dementia, 18(11), 2341-2351. https://doi.org/10.1002/alz.12615 [details]
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Alzheimer s Dementia - 2022 - Temp - A Bayesian perspective on Biogen s aducanumab trial
Supplementary files
alz12615-sup-0001-suppmat

Wagenmakers, E-J., Gronau, Q. F., Dablander, F., & Etz, A. (2022). The Support Interval. Erkenntnis, 87(2), 589–601. Advance online publication. https://doi.org/10.31234/osf.io/zwnxb, https://doi.org/10.1007/s10670-019-00209-z [details]
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TheSupportInterval
Wagenmakers2022 Article TheSupportInterval

2021

Aczel, B., Szaszi, B., Nilsonne, G., van den Akker, O. R., Albers, C. J., van Assen, M. A., Bastiaansen, J. A., Benjamin, D., Boehm, U., Botvinik-Nezer, R., Bringmann, L. F., Busch, N. A., Caruyer, E., Cataldo, A. M., Cowan, N., Delios, A., van Dongen, N. N. N., Donkin, C., van Doorn, J. B., ... Wagenmakers, E.-J. (2021). Science Forum: Consensus-based guidance for conducting and reporting multi-analyst studies. eLife, 10, Article e72185. https://doi.org/10.7554/eLife.72185 [details]
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Bartoš, F., Gronau, Q. F., Timmers, B., Otte, W. M., Ly, A., & Wagenmakers, E.-J. (2021). Bayesian model-averaged meta-analysis in medicine. Statistics in Medicine, 40(30), 6743-6761. https://doi.org/10.1002/sim.9170 [details]
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Derks, K., de Swart, J., Wagenmakers, E-J., Wille, J., & Wetzels, R. (2021). JASP for Audit: Bayesian Tools for the Auditing Practice. The Journal of Open Source Software, 6(68), Article 2733. Advance online publication. https://doi.org/10.21105/joss.02733 [details]
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Derks, K., de Swart, J., van Batenburg, P., Wagenmakers, E.-J., & Wetzels, R. (2021). Priors in a Bayesian audit: How integration of existing information into the prior distribution can improve audit transparency and efficiency. International Journal of Auditing, 25(3), 621-636. https://doi.org/10.1111/ijau.12240 [details]

Dutilh, G., Sarafoglou, A., & Wagenmakers, E-J. (2021). Flexible Yet Fair: Blinding Analyses in Experimental Psychology. Synthese, 198(Supplement issue 23), 5745-5772. Advance online publication. https://doi.org/10.31234/osf.io/d79r8, https://doi.org/10.1007/s11229-019-02456-7 [details]
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Gronau, Q. F., Heck, D. W., Berkhout, S. W., Haaf, J. M., & Wagenmakers, E-J. (2021). A Primer on Bayesian Model-Averaged Meta-Analysis. Advances in Methods and Practices in Psychological Science, 4(3). Advance online publication. https://doi.org/10.1177/25152459211031256 [details]
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Gronau, Q. F., Raj, A. K. N., & Wagenmakers, E-J. (2021). Informed Bayesian Inference for the A/B Test. Journal of Statistical Software, 100(17). Advance online publication. https://doi.org/10.18637/jss.v100.i17 [details]
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v100i17
Supplementary files
abtest 1.0.1.tar
v100i17

Hoffmann, T., Hofman, A. D., & Wagenmakers, E. M. (2021). A Tutorial on Bayesian Inference for the A/B Test with R and JASP. Methodology, 1-50. https://doi.org/10.31234/osf.io/z64th

Hulme, O. J., Wagenmakers, E. J., Damkier, P., Madelung, C. F., Siebner, H. R., Helweg-Larsen, J., Gronau, Q. F., Benfield, T. L., & Madsen, K. H. (2021). A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19. PLoS ONE, 16(2), Article e0245048. https://doi.org/10.1371/journal.pone.0245048 [details]
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Linde, M., Tendeiro, J. N., Selker, R., Wagenmakers, E-J., & van Ravenzwaaij, D. (2021). Decisions about equivalence: A comparison of TOST, HDI-ROPE, and the Bayes factor. Psychological Methods. Advance online publication. https://doi.org/10.1037/met0000402

Manning, C., Wagenmakers, E-J., Norcia, A. M., Scerif, G., & Böhm, U. (2021). Perceptual Decision-Making in Children: Age-Related Differences and EEG Correlates. Computational Brain & Behavior, 4(1), 53-69. Advance online publication. https://doi.org/10.31234/osf.io/jwsmb, https://doi.org/10.1007/s42113-020-00087-7 [details]
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Manning2021 Article PerceptualDecision-MakingInChi
Supplementary files
42113 2020 87 MOESM1 ESM
Related datasets
Manning, C., Norcia, A. M., Scerif, G., Boehm, U. & Wagenmakers, E.-J. (2020). Modelling files supporting the published article: Perceptual decision-making in children: Age-related differences and EEG correlates. Figshare. https://doi.org/10.6084/m9.figshare.11931714
Manning, C., Norcia, A. M., Scerif, G., Boehm, U. & Wagenmakers, E.-J. (2020). EEG data supporting the published article: Perceptual decision-making in children: Age-related differences and EEG correlates.. Figshare. https://doi.org/10.6084/m9.figshare.12378281

Mulder, J., Williams, D. R., Gu, X., Tomarken, A., Böing-Messing, F., Olsson-Collentine, A., Meijerink, M., Menke, J., van Aert, R., Fox, J-P., Hoijtink, H., Rosseel, Y., Wagenmakers, E-J., & van Lissa, C. (2021). BFpack: Flexible Bayes Factor Testing of Scientific Theories in R. Journal of Statistical Software, 100(18). Advance online publication. https://doi.org/10.18637/jss.v100.i18 [details]
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v100i18
Supplementary files
BFpack 1.0.0.tar
v100i18

Steingröver, H., Wabersich, D., & Wagenmakers, E-J. (2021). Modeling Across-Trial Variability in the Wald Drift Rate Parameter. Behavior Research Methods, 53(3), 1060–1076. Advance online publication. https://doi.org/10.3758/s13428-020-01448-7 [details]
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Temp, A. G. M., Lutz, M. W., Trepel, D., Tang, Y., Wagenmakers, E. J., Khachaturian, A. S., & Teipel, S. (2021). How Bayesian statistics may help answer some of the controversial questions in clinical research on Alzheimer's disease. Alzheimer's and Dementia, 17(6), 917-919. https://doi.org/10.1002/alz.12374 [details]

Vohs, K. D., Gronau, Q. F., & Wagenmakers, E. M. (2021). A Multisite Preregistered Paradigmatic Test of the Ego-Depletion Effect. Psychological Science, 32(10), 1566-1581. Advance online publication. https://doi.org/10.31234/osf.io/e497p, https://doi.org/10.1177/0956797621989733 [details]

Wagenmakers, E.-J., Sarafoglou, A., Aarts, S., Albers, C., Algermissen, J., Bahník, Š., van Dongen, N., Hoekstra, R., Moreau, D., van Ravenzwaaij, D., Sluga, A., Stanke, F., Tendeiro, J., & Aczel, B. (2021). Seven steps toward more transparency in statistical practice. Nature Human Behaviour, 5(11), 1473-1480. https://doi.org/10.1038/s41562-021-01211-8 [details]

van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., Etz, A., Evans, N. J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharský, Š., Ly, A., Marsman, M., Matzke, D., Komarlu Narendra Gupta, A. R., Sarafoglou, A., Stefan, A., Voelkel, J. G., & Wagenmakers, E-J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28(3), 813–826. Advance online publication. https://doi.org/10.3758/s13423-020-01798-5 [details]
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Doorn2020 Article TheJASPGuidelinesForConducting
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Example1 TTest Stereograms
Example1 TTest Stereograms
Example2 MixedANOVA Bugs
Example3 Correlation BigFivePersonalityTraits
Example4 InformedTTest FacialFeedback
Example5 Regression BigFivePersonalityTraits

van den Bergh, D., Haaf, J. M., Ly, A., Rouder, J. N., & Wagenmakers, E.-J. (2021). A Cautionary Note on Estimating Effect Size. Advances in Methods and Practices in Psychological Science, 4(1). https://doi.org/10.31234/osf.io/h6pr8, https://doi.org/10.1177/2515245921992035 [details]
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von den Bergh, D., Clyde, M. A., Gupta, A. R. K. N., de Jong, T., Gronau, Q. F., Marsman, M., Ly, A., & Wagenmakers, E.-J. (2021). A tutorial on Bayesian multi-model linear regression with BAS and JASP. Behavior Research Methods, 53(6), 2351-2371. https://doi.org/10.31234/osf.io/pqju6, https://doi.org/10.3758/s13428-021-01552-2 [details]
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2020

Aczel, B., Szaszi, B., Sarafoglou, A., Kekecs, Z., Kucharský, Š., Benjamin, D., Chambers, C. D., Fisher, A., Gelman, A., Gernsbacher, M. A., Ioannidis, J. P., Johnson, E., Jonas, K., Kousta, S., Lilienfeld, S. O., Lindsay, D. S., Morey, C. C., Munafò, M., Newell, B. R., ... Wagenmakers, E. J. (2020). Author Correction: A consensus-based transparency checklist. Nature Human Behaviour, 4(1), 120. https://doi.org/10.1038/s41562-019-0812-2

Boehm, U., van Maanen, L., Evans, N. J., Brown, S. D., & Wagenmakers, E.-J. (2020). A theoretical analysis of the reward rate optimality of collapsing decision criteria. Attention, Perception, and Psychophysics, 82(3), 1520-1534. https://doi.org/10.3758/s13414-019-01806-4 [details]
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Dahrendorf, M., Hoffmann, T., Mittenbühler, M., Wiechert, S., Sarafoglou, A., Matzke, D., & Wagenmakers, E-J. (2020). "Because it is the Right Thing to Do'': Taking Stock of the Peer Reviewers’ Openness Initiative. Journal of European Psychology Students, 11(1), 15-20. https://doi.org/10.31234/osf.io/h39jt, https://doi.org/10.5334/jeps.506 [details]
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Evans, N. J., & Wagenmakers, E-J. (2020). Evidence Accumulation Models: Current Limitations and Future Directions. The Quantitative Methods for Psychology, 16(2), 73-90. https://doi.org/10.31234/osf.io/74df9, https://doi.org/10.20982/tqmp.16.2.p073 [details]
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Evans, N. J., Dutilh, G., Wagenmakers, E-J., & Maas, H. L. J. V. D. (2020). Double responding: A new constraint for models of speeded decision making. Cognitive Psychology, 121, Article 101292. Advance online publication. https://doi.org/10.1016/j.cogpsych.2020.101292 [details]
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1-s2.0-S0010028520300219-main
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1-s2.0-S0010028520300219-mmc1

Faulkenberry, T. J., Ly, A., & Wagenmakers, E.-J. (2020). Bayesian Inference in Numerical Cognition: A Tutorial Using JASP. Journal of Numerical Cognition, 6(2), 231-259. https://doi.org/10.5964/jnc.v6i2.288 [details]
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Field, S. M., Wagenmakers, E-J., Kiers, H. A. L., Hoekstra, R., Ernst, A. F., & van Ravenzwaaij, D. (2020). The effect of preregistration on trust in empirical research findings: results of a registered report. Royal Society Open Science, 7(4), Article 181351. https://doi.org/10.1098/rsos.181351 [details]
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rsos.181351
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rsos181351 review history

Gronau, Q. F., Ly, A., & Wagenmakers, E-J. (2020). Informed Bayesian t-Tests. American Statistician, 74(2), 137-143. Advance online publication. https://doi.org/10.1080/00031305.2018.1562983 [details]
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Informed Bayesian t Tests
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online appendix

Gronau, Q. F., Singmann, H., & Wagenmakers, E-J. (2020). bridgesampling: An R Package for Estimating Normalizing Constants. Journal of Statistical Software, 92(10), Article 10. https://doi.org/10.18637/jss.v092.i10 [details]
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v92i10

Hinne, M., Gronau, Q. F., van den Bergh, D., & Wagenmakers, E-J. (2020). A Conceptual Introduction to Bayesian Model Averaging. Advances in Methods and Practices in Psychological Science, 3(2), 200-215. https://doi.org/10.31234/osf.io/wgb64, https://doi.org/10.1177/2515245919898657 [details]
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Hoogeveen, S., Sarafoglou, A., & Wagenmakers, E-J. (2020). Laypeople Can Predict Which Social-Science Studies Will Be Replicated Successfully. Advances in Methods and Practices in Psychological Science, 3(3), 267-285. https://doi.org/10.1177/2515245920919667 [details]
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Keysers, C., Gazzola, V., & Wagenmakers, E-J. (2020). Author Correction: Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence. Nature Neuroscience, 23(11), 1453. Advance online publication. https://doi.org/10.1038/s41593-020-00710-7

Keysers, C., Gazzola, V., & Wagenmakers, E-J. (2020). Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence. Nature Neuroscience, 23(7), 788-799. https://doi.org/10.1038/s41593-020-0660-4 [details]
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s41593-020-0660-4
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41593 2020 660 MOESM1 ESM

Landy, J. F., Jia, M. L., Ding, I. L., Viganola, D., Tierney, W., Dreber, A., Johannesson, M., Pfeiffer, T., Ebersole, C. R., Gronau, Q. F., Ly, A., van den Bergh, D., Marsman, M., Derks, K., Wagenmakers, E-J., Proctor, A., Bartels, D. M., Bauman, C. W., Brady, W. J., ... Uhlmann, E. L. (2020). Crowdsourcing hypothesis tests: Making transparent how design choices shape research results. Psychological Bulletin, 146(5), 451-479. Advance online publication. https://doi.org/10.1037/bul0000220 [details]
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Ly, A., Stefan, A., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., Kucharský, S., Derks, K., Gronau, Q. F., Raj, A., Boehm, U., van Kesteren, E-J., Hinne, M., Matzke, D., Marsman, M., & Wagenmakers, E-J. (2020). The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test. Computational Brain & Behavior, 3(2), 153-161. Advance online publication. https://doi.org/10.31234/osf.io/dhb7x, https://doi.org/10.1007/s42113-019-00070-x [details]
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Sarafoglou, A., Hoogeveen, S., Matzke, D., & Wagenmakers, E-J. (2020). Teaching Good Research Practices: Protocol of a Research Master Course. Psychology Learning and Teaching, 19(1), 46-59. Advance online publication. https://doi.org/10.1177/1475725719858807 [details]
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Wagenmakers, E-J., Lee, M. D., Rouder, J. N., & Morey, R. D. (2020). The Principle of Predictive Irrelevance, or Why Intervals Should Not be Used for Model Comparison Featuring a Point Null Hypothesis. In C. W. Gruber (Ed.), The Theory of Statistics in Psychology: Applications, Use and Misunderstandings (pp. 111-129). (Annals of Theoretical Psychology; Vol. 16). Springer. https://doi.org/10.31234/osf.io/rqnu5, https://doi.org/10.1007/978-3-030-48043-1_8 [details]
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van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E-J. (2020). Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman’s ρ. Journal of Applied Statistics, 47(16), 2984-3006. https://doi.org/10.1080/02664763.2019.1709053 [details]
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van Doorn, J., Matzke, D., & Wagenmakers, E-J. (2020). An In-Class Demonstration of Bayesian Inference. Psychology Learning and Teaching, 19(1), 36-45. Advance online publication. https://doi.org/10.1177/1475725719848574 [details]
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van den Bergh, D., Bogaerts, S., Spreen, M., Flohr, R., Vandekerckhove, J., Batchelder, W. H., & Wagenmakers, E.-J. (2020). Cultural Consensus Theory for the evaluation of patients’ mental health scores in forensic psychiatric hospitals. Journal of Mathematical Psychology, 98, Article 102383. https://doi.org/10.1016/j.jmp.2020.102383 [details]
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van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E-J., Derks, K., Dablander, F., Gronau, Q. F., Kucharský, Š., Komarlu Narendra Gupta, A. R., Sarafoglou, A., Voelkel, J. G., Stefan, A., Ly, A., Hinne, M., Matzke, D., & Wagenmakers, E-J. (2020). A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP. Année Psychologique, 120(1), 73-96. https://doi.org/10.31234/osf.io/spreb, https://doi.org/10.3917/anpsy1.201.0073 [details]

2019

Evans, N. J., & Wagenmakers, E-J. (2019). Theoretically meaningful models can answer clinically relevant questions. Brain, 142(5), 1172-1175. https://doi.org/10.1093/brain/awz073 [details]
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Gronau, Q. F., & Wagenmakers, E-J. (2019). Limitations of Bayesian Leave-One-Out Cross-Validation for Model Selection. Computational Brain & Behavior, 2(1), 1-11. Advance online publication. https://doi.org/10.1007/s42113-018-0011-7 [details]
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Gronau, Q. F., & Wagenmakers, E-J. (2019). Rejoinder: More Limitations of Bayesian Leave-One-Out Cross-Validation. Computational Brain & Behavior, 2(1), 35-47. https://doi.org/10.1007/s42113-018-0022-4 [details]
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Gronau, Q. F., Wagenmakers, E-J., Heck, D. W., & Matzke, D. (2019). A simple method for comparing complex models: Bayesian model comparison for hierarchical multinomial processing tree models using Warp-III bridge sampling. Psychometrika, 84(1), 261-284. https://doi.org/10.1007/s11336-018-9648-3 [details]
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Gronau2019 Article ASimpleMethodForComparingCompl
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11336 2018 9648 MOESM1 ESM

Heck, D. W., Overstall, A. M., Gronau, Q. F., & Wagenmakers, E.-J. (2019). Quantifying uncertainty in transdimensional Markov chain Monte Carlo using discrete Markov models. Statistics and Computing, 29(4), 631-643. https://doi.org/10.1007/s11222-018-9828-0 [details]
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Love, J., Selker, R., Marsman, M., Jamil, T., Dropmann, D., Verhagen, J., Ly, A., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Wild, A., Knight, P., Rouder, J. N., Morey, R. D., & Wagenmakers, E-J. (2019). JASP: Graphical statistical software for common statistical designs. Journal of Statistical Software, 88, Article 2. https://doi.org/10.18637/jss.v088.i02 [details]
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v88i02
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jasp-desktop-0.9.1
EyeMovements

Ly, A., Etz, A., Marsman, M., & Wagenmakers, E-J. (2019). Replication Bayes factors from evidence updating. Behavior Research Methods, 51(6), 2498–2508. Advance online publication. https://doi.org/10.3758/s13428-018-1092-x [details]
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Marsman, M., Waldorp, L., Dablander, F., & Wagenmakers, E-J. (2019). Bayesian estimation of explained variance in ANOVA designs. Statistica Neerlandica, 73(3), 351-372. https://doi.org/10.1111/stan.12173 [details]
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Selker, R., van den Bergh, D., Criss, A. H., & Wagenmakers, E-J. (2019). Parsimonious estimation of signal detection models from confidence ratings. Behavior Research Methods, 51(5), 1953-1967. https://doi.org/10.3758/s13428-019-01231-3 [details]
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Stefan, A. M., Gronau, Q. F., Schönbrodt, F. D., & Wagenmakers, E-J. (2019). A tutorial on Bayes Factor Design Analysis using an informed prior. Behavior Research Methods, 51(3), 1042-1058. Advance online publication. https://doi.org/10.3758/s13428-018-01189-8 [details]
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van Dongen, N. N. N., van Doorn, J. B., Gronau, Q. F., van Ravenzwaaij, D., Hoekstra, R., Haucke, M. N., Lakens, D., Hennig, C., Morey, R. D., Homer, S., Gelman, A., Sprenger, J., & Wagenmakers, E. J. (2019). Multiple Perspectives on Inference for Two Simple Statistical Scenarios. American Statistician, 73(S1), 328-339. https://doi.org/10.1080/00031305.2019.1565553 [details]
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van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E-J. (2019). Bayesian estimation of Kendall’s τ using a latent normal approach. Statistics and Probability Letters, 145, 268-272. Advance online publication. https://doi.org/10.1016/j.spl.2018.10.004 [details]
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1-s2.0-S0167715218303201-main
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2018

Aczel, B., Palfi, B., Szollosi, A., Kovacs, M., Szaszi, B., Szecsi, P., Zrubka, M., Gronau, Q. F., van den Bergh, D., & Wagenmakers, E-J. (2018). Quantifying Support for the Null Hypothesis in Psychology: An Empirical Investigation. Advances in Methods and Practices in Psychological Science, 1(3), 357-366. https://doi.org/10.1177/2515245918773742 [details]
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2515245918773742
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10 1177 2515245918773742

Beek, T. F., Matzke, D., Pinto, Y., Rotteveel, M., Gierholz, A., Verhagen, J., Selker, R., Sasiadek, A., Steingroever, H., Jostmann, N. B., & Wagenmakers, E-J. (2018). Incidental Haptic Sensations May Not Influence Social Judgments: A Purely Confirmatory Replication Attempt of Study 1 by Ackerman, Nocera, and Bargh (2010). Journal of Articles in Support of the Null Hypothesis, 14(2), 69-90. https://search.ebscohost.com/login.aspx?direct=true&db=aph&AN=132351143&site=ehost-live&scope=site [details]
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Boehm, U., Annis, J., Frank, M. J., Hawkins, G. E., Heathcote, A., Kellen, D., Krypotos, A-M., Lerche, V., Logan, G. D., Palmeri, T. J., van Ravenzwaaij, D., Servant, M., Singmann, H., Starns, J. J., Voss, A., Wiecki, T. V., Matzke, D., & Wagenmakers, E-J. (2018). Estimating across-trial variability parameters of the Diffusion Decision Model: Expert advice and recommendations. Journal of Mathematical Psychology, 87, 46-75. https://doi.org/10.1016/j.jmp.2018.09.004 [details]
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Boehm, U., Marsman, M., Matzke, D., & Wagenmakers, E-J. (2018). On the importance of avoiding shortcuts in applying cognitive models to hierarchical data. Behavior Research Methods, 50(4), 1614-1631. https://doi.org/10.3758/s13428-018-1054-3 [details]
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Boehm, U., Steingroever, H., & Wagenmakers, E.-J. (2018). Using Bayesian regression to test hypotheses about relationships between parameters and covariates in cognitive models. Behavior Research Methods, 50(3), 1248–1269. https://doi.org/10.3758/s13428-017-0940-4 [details]
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Camerer, C., Dreber Almenberg, A., Holzmeister, F., Ho, T-H., Huber, J., Johannesson, M., Kirchler, M., Nave, G., Nosek, B., Pfeiffer, T., Altmejd, A., Buttrick, N., Chan, T., Chen, Y., Forsell, E., Gampa, A., Heikenstein, E., Hummer, L., Imai, T., ... Wu, H. (2018). Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015. Nature Human Behaviour, 2(9), 637–644. https://doi.org/10.1038/s41562-018-0399-z [details]

Derks, K., Burger, J., van Doorn, J., Kossakowski, J. J., Matzke, D., Atticciati, L., Beitner, J., Benzesin, V., de Bruijn, A. L., Cohen, T. R. H., Cordesius, E. P. A., van Dekken, M., Delvendahl, N., Dobbelaar, S., Groenendijk, E. R., Hermans, M. E., Hiekkaranta, A. P., Hoekstra, R. H. A., Hoffmann, A. M., ... Wagenmakers, E-J. (2018). Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance. Journal of European Psychology Students, 9, 48-57. https://doi.org/10.5334/jeps.458 [details]
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Ernst, A. F., Hoekstra, R., Wagenmakers, E.-J., Gelman, A., & van Ravenzwaaij, D. (2018). Do Researchers Anchor Their Beliefs on the Outcome of an Initial Study? Testing the Time-Reversal Heuristic. Experimental Psychology, 65(3), 158-169. https://doi.org/10.1027/1618-3169/a000402 [details]

Gronau, Q. F., & Wagenmakers, E.-J. (2018). Bayesian Evidence Accumulation in Experimental Mathematics: A Case Study of Four Irrational Numbers. Experimental Mathematics, 27(3), 277-286. https://doi.org/10.1080/10586458.2016.1256006 [details]

Hoekstra, R., Monden, R., van Ravenzwaaij, D., & Wagenmakers, E.-J. (2018). Bayesian reanalysis of null results reported in medicine Strong yet variable evidence for the absence of treatment effects. PLoS ONE, 13(4), Article e0195474. https://doi.org/10.1371/journal.pone.0195474 [details]
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journal.pone.0195474.s001
journal.pone.0195474.s002

Hoogeveen, S., Wagenmakers, E.-J., Kay, A. C., & Van Elk, M. (2018). Compensatory control and religious beliefs: A registered replication report across two countries. Comprehensive Results in Social Psychology, 3(3), 240-265. https://doi.org/10.1080/23743603.2019.1684821 [details]
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Houtkoop, B. L., Chambers, C., Macleod, M., Bishop, D. V. M., Nichols, T. E., & Wagenmakers, E-J. (2018). Data sharing in psychology: A survey on barriers and preconditions. Advances in Methods and Practices in Psychological Science, 1(1), 70-85. https://doi.org/10.1177/2515245917751886 [details]

Hu, C-P., Kong, X-Z., Wagenmakers, E-J., Ly, A., & Peng, K. (2018). The Bayes factor and its implementation in JASP: A practical primer. Xinli kexue jinzhan, 26(6), 951–965. https://doi.org/10.3724/SP.J.1042.2018.00951 [details]

Ly, A., Marsman, M., & Wagenmakers, E-J. (2018). Analytic posteriors for Pearson's correlation coefficient. Statistica Neerlandica, 72(1), 4-13. Advance online publication. https://doi.org/10.1111/stan.12111 [details]
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Ly, A., Raj, A., Etz, A., Marsman, M., Gronau, Q. F., & Wagenmakers, E-J. (2018). Bayesian reanalyses from summary statistics: A guide for academic consumers. Advances in Methods and Practices in Psychological Science, 1(3), 367-374. https://doi.org/10.1177/2515245918779348 [details]
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2515245918779348
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LyOpenPracticesDisclosure

Meindertsma, T., Kloosterman, N. A., Engel, A. K., Wagenmakers, E-J., & Donner, T. H. (2018). Surprise About Sensory Event Timing Drives Cortical Transients in the Beta Frequency Band. The Journal of Neuroscience, 38(35), 7600-7610. https://doi.org/10.1523/JNEUROSCI.0307-18.2018 [details]
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Monden, R., Roest, A. M., van Ravenzwaaij, D., Wagenmakers, E.-J., Morey, R., Wardenaar, K. J., & de Jonge, P. (2018). The comparative evidence basis for the efficacy of second-generation antidepressants in the treatment of depression in the US: A Bayesian meta-analysis of Food and Drug Administration reviews. Journal of Affective Disorders, 235, 393-398. https://doi.org/10.1016/j.jad.2018.04.040 [details]
Related datasets
de Jonge, P., Morey, R., Roest, A. M., Wardenaar, K. J., Monden, R., Wagenmakers, E.-J. & van Ravenzwaaij, D. (2018). Data for: The comparative evidence basis for the efficacy of second-generation antidepressants in the treatment of depression: A Bayesian Meta-analysis. Mendeley Data. https://doi.org/10.17632/p3k5h38xpn.1

Schönbrodt, F. D., & Wagenmakers, E-J. (2018). Bayes factor design analysis: Planning for compelling evidence. Psychonomic Bulletin and Review, 25(1), 128-142. https://doi.org/10.3758/s13423-017-1230-y [details]

Silberzahn, R., Uhlmann, E. L., Martin, D. P., Anselmi, P., Aust, F., Awtrey, E., Bahník, Bai, F., Bannard, C., Bonnier, E., Carlsson, R., Cheung, F., Christensen, G., Clay, R., Craig, M. A., Rosa, A. D., Dam, L., Evans, M. H., Cervantes, I. F., ... Nosek, B. A. (2018). Many analysts, one data set: Making transparent how variations in analytic choices affect results. Advances in Methods and Practices in Psychological Science, 1(3), 337-356. https://doi.org/10.1177/2515245917747646
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Wagenmakers, E-J. (2018). In Vivo: Likelihood: A halfway house? In S. Farrell, & S. Lewandowsky (Eds.), Computational Modeling of Cognition and Behaviour (pp. 103-104). Cambridge University Press. https://doi.org/10.1017/CBO9781316272503.005 [details]

Wagenmakers, E-J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Selker, R., Gronau, Q. F., Dropmann, D., Boutin, B., Meerhoff, F., Knight, P., Raj, A., van Kesteren, E-J., van Doorn, J., Šmíra, M., Epskamp, S., Etz, A., Matzke, D., ... Morey, R. D. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25(1), 58-76. Advance online publication. https://doi.org/10.3758/s13423-017-1323-7 [details]
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Wagenmakers, E-J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., Love, J., Selker, R., Gronau, Q. F., Šmíra, M., Epskamp, S., Matzke, D., Rouder, J. N., & Morey, R. D. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25(1), 35-57. Advance online publication. https://doi.org/10.3758/s13423-017-1343-3 [details]
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Wagenmakers, E.-J., Dutilh, G., & Sarafoglou, A. (2018). The Creativity-Verification Cycle in Psychological Science: New Methods to Combat Old Idols. Perspectives on Psychological Science, 13(4), 418-427. https://doi.org/10.1177/1745691618771357 [details]
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van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E-J. (2018). Bayesian Inference for Kendall's Rank Correlation Coefficient. American Statistician, 72(4), 303-308. Advance online publication. https://doi.org/10.1080/00031305.2016.1264998 [details]
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Bayesian Inference for Kendall s Rank Correlation Coefficient
Supplementary files
4452449
1
Related datasets
van Doorn, J., Wagenmakers, E.-J., Eric-Jan, W., Ly, A. & Marsman, M. (2016). Bayesian Inference for Kendall's Rank Correlation Coefficient. Taylor & Francis. https://doi.org/10.6084/m9.figshare.4452449
van Doorn, J., Wagenmakers, E.-J., Eric-Jan, W., Ly, A. & Marsman, M. (2016). Bayesian Inference for Kendall's Rank Correlation Coefficient. Taylor & Francis. https://doi.org/10.6084/m9.figshare.4452449

2017

Dutilh, G., Vandekerckhove, J., Ly, A., Matzke, D., Pedroni, A., Frey, R., Rieskamp, J., & Wagenmakers, E-J. (2017). A test of the diffusion model explanation for the worst performance rule using preregistration and blinding. Attention, Perception & Psychophysics, 79(3), 713-725. https://doi.org/10.3758/s13414-017-1304-y [details]
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Etz, A., & Wagenmakers, E.-J. (2017). J. B. S. Haldane's contribution to the bayes factor hypothesis test. Statistical Science, 32(2), 313-329. https://doi.org/10.1214/16-STS599 [details]
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Evans, N. J., Hawkins, G. E., Boehm, U., Wagenmakers, E-J., & Brown, S. D. (2017). The computations that support simple decision-making: A comparison between the diffusion and urgency-gating models. Scientific Reports, 7, Article 16433. https://doi.org/10.1038/s41598-017-16694-7 [details]
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Forstmeier, W., Wagenmakers, E. J., & Parker, T. H. (2017). Detecting and avoiding likely false-positive findings: A practical guide. Biological Reviews of the Cambridge Philosophical Society, 92(4), 1941–1968. https://doi.org/10.1111/brv.12315 [details]
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Gronau, Q. F., Duizer, M., Bakker, M., & Wagenmakers, E-J. (2017). Bayesian mixture modeling of significant p values: A meta-analytic method to estimate the degree of contamination from H₀. Journal of Experimental Psychology. General, 146(9), 1223-1233. https://doi.org/10.1037/xge0000324 [details]

Gronau, Q. F., Sarafoglou, A., Matzke, D., Ly, A., Boehm, U., Marsman, M., Leslie, D. S., Forster, J. J., Wagenmakers, E-M., & Steingroever, H. (2017). A tutorial on bridge sampling. Journal of Mathematical Psychology, 81, 80-97. Advance online publication. https://doi.org/10.1016/j.jmp.2017.09.005 [details]
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Gronau, Q. F., Van Erp, S., Heck, D. W., Cesario, J., Jonas, K. J., & Wagenmakers, E-J. (2017). A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: the case of felt power. Comprehensive Results in Social Psychology, 2(1), 123-138. https://doi.org/10.1080/23743603.2017.1326760 [details]

Jamil, T., Ly, A., Morey, R. D., Love, J., Marsman, M., & Wagenmakers, E-J. (2017). Default “Gunel and Dickey” Bayes factors for contingency tables. Behavior Research Methods, 49(2), 638-652. Advance online publication. https://doi.org/10.3758/s13428-016-0739-8 [details]
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Jamil, T., Marsman, M., Ly, A., Morey, R. D., & Wagenmakers, E-J. (2017). What Are the Odds? Modern Relevance and Bayes Factor Solutions for MacAlister’s Problem From the 1881 Educational Times. Educational and Psychological Measurement, 77(5), 819-830. Advance online publication. https://doi.org/10.1177/0013164416667980 [details]
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Ly, A., Marsman, M., Verhagen, J., Grasman, R. P. P. P., & Wagenmakers, E-M. (2017). A tutorial on Fisher information. Journal of Mathematical Psychology, 80, 40-55. Advance online publication. https://doi.org/10.1016/j.jmp.2017.05.006 [details]
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Marsman, M., & Wagenmakers, E-J. (2017). Bayesian benefits with JASP. The European Journal of Developmental Psychology, 14(5), 545-555. Advance online publication. https://doi.org/10.1080/17405629.2016.1259614 [details]
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Marsman, M., & Wagenmakers, E-J. (2017). Three insights from a Bayesian interpretation of the one-sided P value. Educational and Psychological Measurement, 77(3), 529-539. Advance online publication. https://doi.org/10.1177/0013164416669201 [details]
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Marsman, M., Schönbrodt, F. D., Morey, R. D., Yao, Y., Gelman, A., & Wagenmakers, E-J. (2017). A Bayesian bird's eye view of 'Replications of important results in social psychology'. Royal Society Open Science, 4(1), Article 160426. https://doi.org/10.1098/rsos.160426, https://doi.org/10.1098/rsos.170085 [details]
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160426.full.pd
170085.full.pd

Matzke, D., Ly, A., Selker, R., Weeda, W. D., Scheibehenne, B., Lee, M. D., & Wagenmakers, E-J. (2017). Bayesian inference for correlations in the presence of measurement error and estimation uncertainty. Collabra: Psychology, 3(1), Article 25. https://doi.org/10.1525/collabra.78 [details]
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Munafò, M. R., Nosek, B. A., Bishop, D. V. M., Button, K. S., Chambers, C. D., Percie Du Sert, N., Simonsohn, U., Wagenmakers, E-J., Ware, J. J., & Ioannidis, J. P. A. (2017). A manifesto for reproducible science. Nature Human Behaviour, 1(1), Article 0021. https://doi.org/10.1038/s41562-016-0021 [details]
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Rouder, J. N., Morey, R. D., Verhagen, J., Swagman, A. R., & Wagenmakers, E. J. (2017). Bayesian analysis of factorial designs. Psychological Methods, 22(2), 304-321. https://doi.org/10.1037/met0000057 [details]

Scheibehenne, B., Gronau, Q. F., Jamil, T., & Wagenmakers, E-J. (2017). Fixed or Random? A Resolution Through Model Averaging: Reply to Carlsson, Schimmack, Williams, and Bürkner (2017). Psychological Science, 28(11), 1698-1701. https://doi.org/10.1177/0956797617724426 [details]

Schönbrodt, F. D., Wagenmakers, E-J., Zehetleitner, M., & Perugini, M. (2017). Sequential Hypothesis Testing With Bayes Factors: Efficiently Testing Mean Differences. Psychological Methods, 22(2), 322-339. Advance online publication. https://doi.org/10.1037/met0000061 [details]

Wagenmakers, E-J., Verhagen, J., Ly, A., Matzke, D., Steingroever, H., Rouder, J. N., & Morey, R. D. (2017). The need for Bayesian hypothesis testing in psychological science. In S. O. Lilienfeld, & I. D. Waldman (Eds.), Psychological Science under Scrutiny: Recent Challenges and Proposed Solutions (pp. 123-138). Wiley Blackwell. https://doi.org/10.1002/9781119095910.ch8 [details]

van Elk, M., & Wagenmakers, E-J. (2017). Can the experimental study of religion be advanced using a Bayesian predictive framework? Religion, Brain & Behavior, 7(4), 331-334. Advance online publication. https://doi.org/10.1080/2153599X.2016.1249915 [details]
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van Erp, S., Verhagen, J., Grasman, R. P. P. P., & Wagenmakers, E-J. (2017). Estimates of Between-Study Heterogeneity for 705 Meta-Analyses Reported in Psychological Bulletin From 1990–2013. Journal of Open Psychology Data, 5(1), Article 4. https://doi.org/10.5334/jopd.33 [details]
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33-301-1-PB
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jopd-5-33-s1
jopd-5-33-s2

2016

Boehm, U., Hawkins, G. E., Brown, S., van Rijn, H., & Wagenmakers, E-J. (2016). Of monkeys and men: Impatience in perceptual decision-making. Psychonomic Bulletin & Review, 23(3), 738-749. Advance online publication. https://doi.org/10.3758/s13423-015-0958-5 [details]
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Boekel, W., Forstmann, B. U., & Wagenmakers, E-J. (2016). Challenges in replicating brain-behavior correlations: Rejoinder to Kanai (2015) and Muhlert and Ridgway (2015). Cortex, 74, 348-352. https://doi.org/10.1016/j.cortex.2015.06.018 [details]
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Cramer, A. O. J., van Ravenzwaaij, D., Matzke, D., Steingroever, H., Wetzels, R., Grasman, R. P. P. P., Waldorp, L. J., & Wagenmakers, E-J. (2016). Hidden multiplicity in exploratory multiway ANOVA: Prevalence and remedies. Psychonomic Bulletin & Review, 23(2), 640-647. Advance online publication. https://doi.org/10.3758/s13423-015-0913-5 [details]
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Field, S. M., Wagenmakers, E.-J., Newell, B. R., Zeelenberg, R., & van Ravenzwaaij, D. (2016). Two Bayesian tests of the GLOMO^sys model. Journal of Experimental Psychology. General, 145(12), e81-e95. https://doi.org/10.1037/xge0000067 [details]

Forstmann, B. U., Ratcliff, R., & Wagenmakers, E-J. (2016). Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions. Annual Review of Psychology, 67, 641-666. Advance online publication. https://doi.org/10.1146/annurev-psych-122414-033645 [details]
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Heck, D. W., & Wagenmakers, E-J. (2016). Adjusted priors for Bayes factors involving reparameterized order constraints. Journal of Mathematical Psychology, 73, 110-116. Advance online publication. https://doi.org/10.1016/j.jmp.2016.05.004 [details]

Ly, A., Verhagen, J., & Wagenmakers, E-J. (2016). An evaluation of alternative methods for testing hypotheses, from the perspective of Harold Jeffreys. Journal of Mathematical Psychology, 72, 43-55. Advance online publication. https://doi.org/10.1016/j.jmp.2016.01.003 [details]

Ly, A., Verhagen, J., & Wagenmakers, E-J. (2016). Harold Jeffreys’s default Bayes factor hypothesis tests: Explanation, extension, and application in psychology. Journal of Mathematical Psychology, 72, 19-32. https://doi.org/10.1016/j.jmp.2015.06.004 [details]

Monden, R., de Vos, S., Morey, R., Wagenmakers, E-J., de Jonge, P., & Roest, A. M. (2016). Toward evidence-based medical statistics: A Bayesian analysis of double-blind placebo-controlled antidepressant trials in the treatment of anxiety disorders. International Journal of Methods in Psychiatric Research, 25(4), 299-308. https://doi.org/10.1002/mpr.1507 [details]

Morey, R. D., Chambers, C. D., Etchells, P. J., Harris, C. R., Hoekstra, R., Lakens, D., Lewandowsky, S., Morey, C. C., Newman, D. P., Schönbrodt, F. D., Vanpaemel, W., Wagenmakers, E-J., & Zwaan, R. A. (2016). The Peer Reviewers’ Openness Initiative: incentivizing open research practices through peer review. Royal Society Open Science, 3(1), Article 150547. https://doi.org/10.1098/rsos.150547 [details]
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Morey, R. D., Hoekstra, R., Rouder, J. N., Lee, M. D., & Wagenmakers, E-J. (2016). The fallacy of placing confidence in confidence intervals. Psychonomic Bulletin & Review, 23(1), 103-123. Advance online publication. https://doi.org/10.3758/s13423-015-0947-8 [details]
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The fallacy of placing confidence in confidence intervals
13423 2015 947 MOESM1 ESM

Morey, R. D., Wagenmakers, E-J., & Rouder, J. N. (2016). Calibrated Bayes Factors Should Not Be Used: A Reply to Hoijtink, van Kooten, and Hulsker. Multivariate Behavioral Research, 51(1), 11-19. https://doi.org/10.1080/00273171.2015.1052710 [details]
Related datasets
Morey, R. D., Rouder, J. N. & Wagenmakers, E.-J. (2016). Calibrated Bayes Factors Should Not Be Used: A Reply to Hoijtink, van Kooten, and Hulsker. Taylor & Francis. https://doi.org/10.6084/m9.figshare.2252938.v1
Morey, R. D., Rouder, J. N. & Wagenmakers, E.-J. (2016). Calibrated Bayes Factors Should Not Be Used: A Reply to Hoijtink, van Kooten, and Hulsker. Taylor & Francis. https://doi.org/10.6084/m9.figshare.2252938.v1

Mulder, J., & Wagenmakers, E-J. (2016). Editors’ introduction to the special issue “Bayes factors for testing hypotheses in psychological research: Practical relevance and new developments”. Journal of Mathematical Psychology, 72, 1-5. https://doi.org/10.1016/j.jmp.2016.01.002 [details]

Rouder, J. N., Morey, R. D., & Wagenmakers, E-J. (2016). The interplay between subjectivity, statistical practice, and psychological science. Collabra, 2, Article 6. https://doi.org/10.1525/collabra.28 [details]
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Rouder, J. N., Morey, R. D., Verhagen, J., Province, J. M., & Wagenmakers, E-J. (2016). Is there a free lunch in inference? Topics in Cognitive Science, 8(3), 520-547. https://doi.org/10.1111/tops.12214 [details]

Scheibehenne, B., Jamil, T., & Wagenmakers, E. J. (2016). Bayesian Evidence Synthesis Can Reconcile Seemingly Inconsistent Results: The Case of Hotel Towel Reuse. Psychological Science, 27(7), 1043-1046. https://doi.org/10.1177/0956797616644081 [details]

Schweinsberg, M., Madan, N., Vianello, M., Sommer, S. A., Jordan, J., Tierney, W., Awtrey, E., Zhu, L. L., Diermeier, D., Heinze, J. E., Srinivasan, M., Tannenbaum, D., Bivolaru, E., Dana, J., Davis-Stober, C. P., du Plessis, C., Gronau, Q. F., Hafenbrack, A. C., Liao, E. Y., ... Uhlmann, E. L. (2016). The pipeline project: Pre-publication independent replications of a single laboratory's research pipeline. Journal of Experimental Social Psychology, 66, 55-67. Advance online publication. https://doi.org/10.1016/j.jesp.2015.10.001 [details]
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The pipeline project
495016 mmc1

Steingroever, H., Wetzels, R., & Wagenmakers, E-J. (2016). Bayes factors for reinforcement-learning models of the Iowa Gambling Task. Decision, 3(2), 115-131. https://doi.org/10.1037/dec0000040 [details]

Tierney, W., Schweinsberg, M., Jordan, J., Kennedy, D. M., Qureshi, I., Sommer, S. A., Thornley, N., Madan, N., Vianello, M., Awtrey, E., Zhu, L. L., Diermeier, D., Heinze, J. E., Srinivasan, M., Tannenbaum, D., Bivolaru, E., Dana, J., Davis-Stober, C. P., du Plessis, C., ... Uhlmann, E. L. (2016). Data from a pre-publication independent replication initiative examining ten moral judgement effects. Scientific Data, 3, Article 160082. https://doi.org/10.1038/sdata.2016.82 [details]
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Data from a pre-publication independent replication initiative examining ten moral judgement effects
sdata201682-s1
sdata201682-s2

Vandekerckhove, J., & Wagenmakers, E-J. (2016). C. S. Peirce on the Crisis of Confidence and the “No More Bets” Heuristic. The Winnower, 3, Article e146611.14253. https://doi.org/10.15200/winn.146611.14253 [details]
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Wagenmakers, E-J., & Busato, V. (2016). De verleidingen van foponderzoek. Skepter, 29(4), 24-28. https://skepsis.nl/skepter-covers/skepter-29-4-2016/ [details]

Wagenmakers, E-J., Morey, R. D., & Lee, M. D. (2016). Bayesian Benefits for the Pragmatic Researcher. Current Directions in Psychological Science, 25(3), 169-176. https://doi.org/10.1177/0963721416643289 [details]
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Wagenmakers, E-J., Verhagen, J., & Ly, A. (2016). How to quantify the evidence for the absence of a correlation. Behavior Research Methods, 48(2), 413-426. https://doi.org/10.3758/s13428-015-0593-0 [details]
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Wagenmakers, E.-J., Beek, T., Dijkhoff, L., Gronau, Q. F., Acosta, A., Adams, R. B., Albohn, D. N., Allard, E. S., Benning, S. D., Blouin-Hudon, E.-M., Bulnes, L. C., Caldwell, T. L., Calin-Jageman, R. J., Capaldi, C. A., Carfagno, N. S., Chasten, K. T., Cleeremans, A., Connell, L., DeCicco, J. M., ... Zwaan, R. A. (2016). Registered Replication Report: Strack, Martin, & Stepper (1988). Perspectives on Psychological Science, 11(6), 917-928. https://doi.org/10.1177/1745691616674458 [details]
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Wetzels, R., Tutschkow, D., Dolan, C., van der Sluis, S., Dutilh, G., & Wagenmakers, E-J. (2016). A Bayesian test for the hot hand phenomenon. Journal of Mathematical Psychology, 72, 200-209. Advance online publication. https://doi.org/10.1016/j.jmp.2015.12.003 [details]

van Maanen, L., Forstmann, B. U., Keuken, M. C., Wagenmakers, E-J., & Heathcote, A. (2016). The impact of MRI scanner environment on perceptual decision-making. Behavior Research Methods, 48(1), 184-200. Advance online publication. https://doi.org/10.3758/s13428-015-0563-6 [details]
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2015

Aarts, A. A., et al., U., Borsboom, D., Columbus, S., den Bezemer, B., Deserno, M. K., Epskamp, S., Jonas, K., Kleinberg, B., Kossakowski, J. J., Kunkels, Y. K., Rahal, R.-M., Sahin, O., Skorinko, J. L. M., Tio, P., van Bork, R., van den Bergh, D., van Renswoude, D. R., van Doorn, J., & Wagenmakers, E.-J. (2015). Estimating the reproducibility of psychological science. Science, 349(6251), 943. Article aac4716. https://doi.org/10.1126/science.aac4716 [details]
Related datasets
Tio, P., Renkewitz, F., Bell, R., Selterman, D., Thomas, S. L., Martinez, T., Voracek, M., Van Doorn, J., Ostkamp, L., Galak, J., Pipitone, R. ., Epskamp, S., Hodsoll, J., Axt, J., Van Rijn, H., Bartmess, E., Strohminger, N., Beyan, L., Hung, C. O.-Y., … Scholz, S. (1-1-2015). Data from: Estimating the reproducibility of psychological science. Singapore Management University. https://doi.org/10.25440/smu.12062757.v1

Andraszewicz, S., Scheibehenne, B., Rieskamp, J., Grasman, R., Verhagen, J., & Wagenmakers, E-J. (2015). An introduction to Bayesian hypothesis testing for management research. Journal of Management, 41(2), 521-543. Advance online publication. https://doi.org/10.1177/0149206314560412 [details]
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436852
Supplementary files
JOM560412 SupplMat

Boekel, W., Wagenmakers, E-J., Belay, L., Verhagen, J., Brown, S., & Forstmann, B. U. (2015). A purely confirmatory replication study of structural brain-behavior correlations. Cortex, 66, 115-133. https://doi.org/10.1016/j.cortex.2014.11.019 [details]
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439368
Supplementary files
1-s2.0-S0010945215000155-mmc1

Forstmann, B. U., & Wagenmakers, E-J. (2015). Model-based cognitive neuroscience: a conceptual introduction. In B. U. Forstmann, & E-J. Wagenmakers (Eds.), An introduction to model-based cognitive neuroscience (pp. 139-156). Springer. https://doi.org/10.1007/978-1-4939-2236-9_7 [details]
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Forstmann, B. U., & Wagenmakers, E.-J. (2015). Preface. In B. U. Forstmann, & E.-J. Wagenmakers (Eds.), An introduction to model-based cognitive neuroscience (pp. v-vi). Springer. https://doi.org/10.1007/978-1-4939-2236-9 [details]
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Hawkins, G. E., Forstmann, B. U., Wagenmakers, E-J., Ratcliff, R., & Brown, S. D. (2015). Revisiting the evidence of collapsing boundaries and urgency signals in perceptual decision-making. The Journal of Neuroscience, 35(6), 2476-2484. https://doi.org/10.1523/JNEUROSCI.2410-14.2015 [details]
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Hawkins, G. E., Wagenmakers, E.-J., Ratcliff, R., & Brown, S. D. (2015). Discriminating evidence accumulation from urgency signals in speeded decision making. Journal of Neurophysiology, 114(1), 40-47. https://doi.org/10.1152/jn.00088.2015 [details]

Heathcote, A., Brown, S. D., & Wagenmakers, E-J. (2015). An introduction to good practices in cognitive modeling. In B. U. Forstmann, & E-J. Wagenmakers (Eds.), An introduction to model-based cognitive neuroscience (pp. 25-48). Springer. https://doi.org/10.1007/978-1-4939-2236-9_2 [details]

Heck, D. W., Wagenmakers, E-J., & Morey, R. D. (2015). Testing order constraints: Qualitative differences between Bayes factors and normalized maximum likelihood. Statistics & Probability Letters, 105, 157-162. Advance online publication. https://doi.org/10.1016/j.spl.2015.06.014 [details]

Krypotos, A-M., Beckers, T., Kindt, M., & Wagenmakers, E. J. (2015). A Bayesian hierarchical diffusion model decomposition of performance in approach-avoidance tasks. Cognition & Emotion, 29(8), 1424-1444. Advance online publication. https://doi.org/10.1080/02699931.2014.985635 [details]
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436226
Supplementary files
436226 supplemental

Lee, M. D., Lodewyckx, T., & Wagenmakers, E-J. (2015). Three Bayesian analyses of memory deficits in patients with dissociative identity disorder. In J. G. W. Raaijmakers, A. H. Criss, R. L. Goldstone, R. M. Nosofsky, & M. Steyvers (Eds.), Cognitive modeling in perception and memory: a festschrift for Richard M. Shiffrin (pp. 189-200). (Psychology Press festschrifts). Psychology Press. https://webfiles.uci.edu/mdlee/DID.pdf [details]

Love, J., Selker, R., Verhagen, J., Marsman, M., Gronau, Q. F., Jamil, T., Smira, M., Epskamp, S., Wild, A., Ly, A., Matzke, D., Wagenmakers, E-J., Morey, R. D., & Rouder, J. N. (2015). Software to sharpen your stats. APS Observer, 28(3), 27-29. http://www.psychologicalscience.org/index.php/publications/observer/2015/march-15/bayes-or-bust-with-new-softwares.html [details]
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Matzke, D., Dolan, C. V., Batchelder, W. H., & Wagenmakers, E-J. (2015). Bayesian estimation of multinomial processing tree models with heterogeneity in participants and items. Psychometrika, 80(1), 205-235. Advance online publication. https://doi.org/10.1007/s11336-013-9374-9 [details]
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Matzke, D., Nieuwenhuis, S., van Rijn, H., Slagter, H. A., van der Molen, M. W., & Wagenmakers, E-J. (2015). The effect of horizontal eye movements on free recall: A preregistered adversarial collaboration. Journal of Experimental Psychology. General, 144(1), e1-e15. https://doi.org/10.1037/xge0000038 [details]
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Nieuwenstein, M. R., Wierenga, T., Morey, R. D., Wicherts, J. M., Blom, T. N., Wagenmakers, E-J., & van Rijn, H. (2015). On making the right choice: A meta-analysis and large-scale replication attempt of the unconscious thought advantage. Judgment and Decision Making, 10(1), 1-17. http://journal.sjdm.org/14/14321/jdm14321.html [details]
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494286
Supplementary files
494286 supplement

Nosek, B. A., Alter, G., Banks, G. C., Borsboom, D., Bowman, S. D., Breckler, S. J., Buck, S., Chambers, C. D., Chin, G., Christensen, G., Contestabile, M., Dafoe, A., Eich, E., Freese, J., Glennerster, R., Goroff, D., Green, D. P., Hesse, B., Humphreys, M., ... Yarkoni, T. (2015). Promoting an open research culture. Science, 348(6242), 1422-1425. https://doi.org/10.1126/science.aab2374 [details]

Nuijten, M. B., Wetzels, R., Matzke, D., Dolan, C. V., & Wagenmakers, E-J. (2015). A default Bayesian hypothesis test for mediation. Behavior Research Methods, 47(1), 85-97. Advance online publication. https://doi.org/10.3758/s13428-014-0470-2 [details]
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437737
Supplementary files
13428 2014 470 MOESM1 ESM
13428 2014 470 MOESM2 ESM
13428 2014 470 MOESM3 ESM

Rotteveel, M., Gierholz, A., Koch, G., van Aalst, C., Pinto, Y., Matzke, D., Steingroever, H., Verhagen, J., Beek, T. F., Selker, R., Sasiadek, A., & Wagenmakers, E-J. (2015). On the automatic link between affect and tendencies to approach and avoid: Chen and Bargh (1999) revisited. Frontiers in Psychology, 6, Article 335. https://doi.org/10.3389/fpsyg.2015.00335 [details]
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494112
Supplementary files
494112 supplement

Steingroever, H., Fridberg, D., Horstmann, A., Kjome, K., Kumari, V., Lane, S. D., Maia, T., McClelland, J., Pachur, T., Premkumar, P., Stout, J., Wetzels, R., Wood, S., Worthy, D. A., & Wagenmakers, E-J. (2015). Data from 617 healthy participants performing the Iowa gambling task: A "many labs" collaboration. Journal of Open Psychology Data, 3(1), Article e5. https://doi.org/10.5334/jopd.ak [details]
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Steingroever, H., Wetzels, R., & Wagenmakers, E-J. (2015). ŵ=.2, â=.8, ĉ=.6: So what? On the meaning of parameter estimates from reinforcement-learning models. Decision, 2(3), 228-235. https://doi.org/10.1037/dec0000034 [details]

Terry, A., Marley, A. A. J., Barnwal, A., Wagenmakers, E. J., Heathcote, A., & Brown, S. D. (2015). Generalising the drift rate distribution for linear ballistic accumulators. Journal of Mathematical Psychology, 68-69, 49-58. https://doi.org/10.1016/j.jmp.2015.09.002 [details]

Vandekerckhove, J., Matzke, D., & Wagenmakers, E-J. (2015). Model comparison and the principle of parsimony. In J. R. Busemeyer, Z. Wang, J. T. Townsend, & A. Eidels (Eds.), The Oxford handbook of computational and mathematical psychology (pp. 300-319). (Oxford library of psychology). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199957996.013.14 [details]

Wagenmakers, E-J., Beek, T. F., Rotteveel, M., Gierholz, A., Matzke, D., Steingroever, H., Ly, A., Verhagen, J., Selker, R., Sasiadek, A., Gronau, Q. F., Love, J., & Pinto, Y. (2015). Turning the hands of time again: a purely confirmatory replication study and a Bayesian analysis. Frontiers in Psychology, 6, Article 494. https://doi.org/10.3389/fpsyg.2015.00494 [details]
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Wagenmakers, E-J., Verhagen, J., Ly, A., Bakker, M., Lee, M. D., Matzke, D., Rouder, J. N., & Morey, R. D. (2015). A power fallacy. Behavior Research Methods, 47(4), 913-917. https://doi.org/10.3758/s13428-014-0517-4 [details]
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Wagenmakers, E-J., Wetzels, R., Borsboom, D., Kievit, R. A., & van der Maas, H. L. J. (2015). A skeptical eye on psi. In E. C. May, & S. B. Marwaha (Eds.), Extrasensory perception: Support, skepticism, and science (pp. 153-176). Praeger. https://doi.org/10.31234/osf.io/syq2h [details]
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Wagenmakers, E.-J. (2015). A quartet of interactions. Cortex, 73, 334-335. https://doi.org/10.1016/j.cortex.2015.07.031 [details]

van Elk, M., Matzke, D., Gronau, Q. F., Guan, M., Vandekerckhove, J., & Wagenmakers, E-J. (2015). Meta-analyses are no substitute for registered replications: a skeptical perspective on religious priming. Frontiers in Psychology, 6, Article 1365. https://doi.org/10.3389/fpsyg.2015.01365 [details]
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2014

Heathcote, A., Wagenmakers, E-J., & Brown, S. D. (2014). The falsifiability of actual decision-making models. Psychological Review, 121(4), 676-678. https://doi.org/10.1037/a0037771 [details]

Hoekstra, R., Morey, R. D., Rouder, J. N., & Wagenmakers, E-J. (2014). Robust misinterpretation of confidence intervals. Psychonomic Bulletin & Review, 21(5), 1157-1164. Advance online publication. https://doi.org/10.3758/s13423-013-0572-3 [details]

Logan, G. D., van Zandt, T., Verbruggen, F., & Wagenmakers, E-J. (2014). On the ability to inhibit thought and action: General and special theories of an act of control. Psychological Review, 121(1), 66-95. https://doi.org/10.1037/a0035230 [details]

Morey, R. D., & Wagenmakers, E-J. (2014). Simple relation between Bayesian order-restricted and point-null hypothesis tests. Statistics & Probability Letters, 92, 121-124. Advance online publication. https://doi.org/10.1016/j.spl.2014.05.010 [details]

Morey, R. D., Rouder, J. N., Verhagen, J., & Wagenmakers, E-J. (2014). Why hypothesis tests are essential for psychological science: A comment on Cumming (2014). Psychological Science, 25(6), 1289-1290. Advance online publication. https://doi.org/10.1177/0956797614525969 [details]

Munafò, M., Noble, S., Browne, W. J., Brunner, D., Button, K., Ferreira, J., Holmans, P., Langbehn, D., Lewis, G., Lindquist, M., Tilling, K., Wagenmakers, E-J., & Blumenstein, R. (2014). Scientific rigor and the art of motorcycle maintenance. Nature Biotechnology, 32(9), 871-873. Advance online publication. https://doi.org/10.1038/nbt.3004 [details]

Steingroever, H., & Wagenmakers, E-J. (2014). Performance and awareness in the Iowa Gambling Task. Behavioral and Brain Sciences, 37(1), 41-42. Advance online publication. https://doi.org/10.1017/S0140525X13000861 [details]

Steingroever, H., Wetzels, R., & Wagenmakers, E-J. (2014). Absolute performance of reinforcement-learning models for the Iowa Gambling Task. Decision, 1(3), 161-183. https://doi.org/10.1037/dec0000005 [details]

Verhagen, J., & Wagenmakers, E-J. (2014). Bayesian tests to quantify the result of a replication attempt. Journal of Experimental Psychology. General, 143(4), 1457-1475. https://doi.org/10.1037/a0036731 [details]
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Wagenmakers, E-J., & Forstmann, B. U. (2014). Rewarding high-power replication research. Cortex, 51, 105-106. Advance online publication. https://doi.org/10.1016/j.cortex.2013.09.010 [details]

Winkel, J., Keuken, M. C., van Maanen, L., Wagenmakers, E. J., & Forstmann, B. U. (2014). Early evidence affects later decisions: Why evidence accumulation is required to explain response time data. Psychonomic Bulletin & Review, 21(3), 777-784. https://doi.org/10.3758/s13423-013-0551-8 [details]

Zhang, S., Lee, M. D., Vandekerckhove, J., Maris, G., & Wagenmakers, E-J. (2014). Time-varying boundaries for diffusion models of decision making and response time. Frontiers in Psychology, 5, Article 1364. https://doi.org/10.3389/fpsyg.2014.01364 [details]
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de Groot, A. D., Wagenmakers, E-J., Borsboom, D., Verhagen, J., Kievit, R., Bakker, M., Cramer, A., Matzke, D., Mellenbergh, D., & van der Maas, H. L. J. (2014). The meaning of "significance" for different types of research. Acta Psychologica, 148, 188-194. Advance online publication. https://doi.org/10.1016/j.actpsy.2014.02.001 [details]

de Hollander, G., Wagenmakers, E-J., Waldorp, L., & Forstmann, B. (2014). An antidote to the imager's fallacy, or how to identify brain areas that are in limbo. PLoS ONE, 9(12), Article e115700. https://doi.org/10.1371/journal.pone.0115700 [details]
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van Ravenzwaaij, D., Boekel, W., Forstmann, B. U., Ratcliff, R., & Wagenmakers, E-J. (2014). Action video games do not improve the speed of information processing in simple perceptual tasks. Journal of Experimental Psychology. General, 143(5), 1794-1805. https://doi.org/10.1037/a0036923 [details]

2013

Dutilh, G., Forstmann, B., Vandekerckhove, J., & Wagenmakers, E-J. (2013). A diffusion model account of age differences in post-error slowing. Psychology and Aging, 28(1), 64-76. https://doi.org/10.1037/a0029875 [details]

Matzke, D., Dolan, C. V., Logan, G. D., Brown, S. D., & Wagenmakers, E-J. (2013). Bayesian parametric estimation of stop-signal reaction time distributions. Journal of Experimental Psychology. General, 142(4), 1047-1073. Advance online publication. https://doi.org/10.1037/a0030543 [details]

Matzke, D., Love, J., Wiecki, T. V., Brown, S. D., Logan, G. D., & Wagenmakers, E-J. (2013). Release the BEESTS: Bayesian Estimation of Ex-Gaussian STop-Signal reaction time distributions. Frontiers in Psychology, 4, Article 918. https://doi.org/10.3389/fpsyg.2013.00918 [details]
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Mulder, M. J., Keuken, M. C., van Maanen, L., Boekel, W. E., Forstmann, B. U., & Wagenmakers, E. J. (2013). The speed and accuracy of perceptual decisions in a random-tone pitch task. Attention, Perception & Psychophysics, 75(5), 1048-1058. https://doi.org/10.3758/s13414-013-0447-8 [details]

Scheibehenne, B., Rieskamp, J., & Wagenmakers, E-J. (2013). Testing adaptive toolbox models: a Bayesian hierarchical approach. Psychological Review, 120(1), 39-64. https://doi.org/10.1037/a0030777 [details]

Steingroever, H., Wetzels, R., & Wagenmakers, E-J. (2013). A comparison of reinforcement learning models for the Iowa Gambling Task using parameter space partitioning. The Journal of Problem Solving, 5(2), 2. Article 2. https://doi.org/10.7771/1932-6246.1150 [details]
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Steingroever, H., Wetzels, R., & Wagenmakers, E-J. (2013). Validating the PVL-Delta model for the Iowa gambling task. Frontiers in Psychology, 4, Article 898. https://doi.org/10.3389/fpsyg.2013.00898 [details]
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Steingroever, H., Wetzels, R., Horstmann, A., Neumann, J., & Wagenmakers, E-J. (2013). Performance of healthy participants on the Iowa Gambling Task. Psychological Assessment, 25(1), 180-193. https://doi.org/10.1037/a0029929 [details]

Turner, B. M., Forstmann, B. U., Wagenmakers, E-J., Brown, S. D., Sederberg, P. B., & Steyvers, M. (2013). A Bayesian framework for simultaneously modeling neural and behavioral data. NeuroImage, 72, 193-206. Advance online publication. https://doi.org/10.1016/j.neuroimage.2013.01.048 [details]

2012

Dutilh, G., Vandekerckhove, J., Forstmann, B. U., Keuleers, E., Brysbaert, M., & Wagenmakers, E-J. (2012). Testing theories of post-error slowing. Attention, Perception & Psychophysics, 74(2), 454-465. https://doi.org/10.3758/s13414-011-0243-2 [details]

Dutilh, G., van Ravenzwaaij, D., Nieuwenhuis, S., van der Maas, H. L. J., Forstmann, B. U., & Wagenmakers, E-J. (2012). How to measure post-error slowing: A confound and a simple solution. Journal of Mathematical Psychology, 56(3), 208-216. https://doi.org/10.1016/j.jmp.2012.04.001 [details]

Dyjas, O., Grasman, R. P. P. P., Wetzels, R., van der Maas, H. L. J., & Wagenmakers, E-J. (2012). What's in a name: a Bayesian hierarchical analysis of the name-letter effect. Frontiers in Psychology, 3, Article 334. https://doi.org/10.3389/fpsyg.2012.00334 [details]
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Hawkins, G. E., Brown, S. D., Steyvers, M., & Wagenmakers, E-J. (2012). An optimal adjustment procedure to minimize experiment time in decisions with multiple alternatives. Psychonomic Bulletin & Review, 19(2), 339-348. https://doi.org/10.3758/s13423-012-0216-z [details]

Hawkins, G., Brown, S. D., Steyvers, M., & Wagenmakers, E-J. (2012). Context effects in multi-alternative decision making: Empirical data and a Bayesian model. Cognitive Science, 36(3), 498-516. https://doi.org/10.1111/j.1551-6709.2011.01221.x [details]

Hawkins, G., Brown, S. D., Steyvers, M., & Wagenmakers, E-J. (2012). Decision speed induces context effects in choice. Experimental Psychology, 59(4), 206-215. Advance online publication. https://doi.org/10.1027/1618-3169/a000145 [details]

Ho, T., Brown, S., van Maanen, L., Forstmann, B. U., Wagenmakers, E-J., & Serences, J. T. (2012). The optimality of sensory processing during the speed-accuracy tradeoff. The Journal of Neuroscience, 32(23), 7992-8003. https://doi.org/10.1523/JNEUROSCI.0340-12.2012 [details]

Huizenga, H. M., Wetzels, R., van Ravenzwaaij, D., & Wagenmakers, E-J. (2012). Four empirical tests of Unconscious Thought Theory. Organizational Behavior and Human Decision Processes, 117(2), 332-340. https://doi.org/10.1016/j.obhdp.2011.11.010 [details]

Jepma, M., Wagenmakers, E-J., & Nieuwenhuis, S. (2012). Temporal expectation and information processing: A model-based analysis. Cognition, 122(3), 426-441. Advance online publication. https://doi.org/10.1016/j.cognition.2011.11.014 [details]

Mulder, M. J., Wagenmakers, E-J., Ratcliff, R., Boekel, W., & Forstmann, B. U. (2012). Bias in the brain: A diffusion model analysis of prior probability and potential payoff. The Journal of Neuroscience, 32(7), 2335-2343. https://doi.org/10.1523/JNEUROSCI.4156-11.2012 [details]

Ortega, A., Wagenmakers, E-J., Lee, M. D., Markowitsch, H. J., & Piefke, M. (2012). A Bayesian latent group analysis for detecting poor effort in the assessment of malingering. Archives of Clinical Neuropsychology, 27(4), 453-465. Advance online publication. https://doi.org/10.1093/arclin/acs038 [details]

Wagenmakers, E-J., Krypotos, A-M., Criss, A. H., & Iverson, G. (2012). On the interpretation of removable interactions: a survey of the field 33 years after Loftus. Memory & Cognition, 40(2), 145-160. https://doi.org/10.3758/s13421-011-0158-0 [details]
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Wagenmakers, E-J., Wetzels, R., Borsboom, D., van der Maas, H. L. J., & Kievit, R. A. (2012). An agenda for purely confirmatory research. Perspectives on Psychological Science, 7(6), 632-638. https://doi.org/10.1177/1745691612463078 [details]

Wagenmakers, E-J., van der Maas, H. L. J., & Farrell, S. (2012). Abstract concepts require concrete models: Why cognitive scientists have not yet embraced nonlinearly coupled, dynamical, self-organized critical, synergistic, scale-free, exquisitely context-sensitive, interaction-dominant, multifractal, interdependent brain-body-niche systems. Topics in Cognitive Science, 4(1), 87-93. Advance online publication. https://doi.org/10.1111/j.1756-8765.2011.01164.x [details]

Wetzels, R., & Wagenmakers, E. J. (2012). A default Bayesian hypothesis test for correlations and partial correlations. Psychonomic Bulletin & Review, 19(6), 1057-1064. https://doi.org/10.3758/s13423-012-0295-x [details]
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Wetzels, R., Grasman, R. P. P. P., & Wagenmakers, E. J. (2012). A default Bayesian hypothesis test for ANOVA designs. American Statistician, 66(2), 104-111. https://doi.org/10.1080/00031305.2012.695956 [details]

van Maanen, L., Grasman, R. P. P. P., Forstmann, B. U., & Wagenmakers, E-J. (2012). Piéron's law and optimal behavior in perceptual decision-making. Frontiers in Neuroscience, 5, Article 143. https://doi.org/10.3389/fnins.2011.00143 [details]
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van Maanen, L., Grasman, R. P. P. P., Forstmann, B. U., Keuken, M. C., Brown, S. D., & Wagenmakers, E-J. (2012). Similarity and number of alternatives in the random-dot motion paradigm. Attention, Perception & Psychophysics, 74(4), 739-753. https://doi.org/10.3758/s13414-011-0267-7 [details]

van Ravenzwaaij, D., Dutilh, G., & Wagenmakers, E-J. (2012). A diffusion model decomposition of the effects of alcohol on perceptual decision making. Psychopharmacology, 219(4), 1017-1025. https://doi.org/10.1007/s00213-011-2435-9 [details]

van Ravenzwaaij, D., Mulder, M. J., Tuerlinckx, F., & Wagenmakers, E-J. (2012). Do the dynamics of prior information depend on task context? An analysis of optimal performance and an empirical test. Frontiers in Psychology, 3, Article 132. https://doi.org/10.3389/fpsyg.2012.00132 [details]
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van Ravenzwaaij, D., van der Maas, H. L. J., & Wagenmakers, E-J. (2012). Optimal decision making in neural inhibition models. Psychological Review, 119(1), 201-215. https://doi.org/10.1037/a0026275 [details]

2011

Donkin, C., Brown, S., Heathcote, A., & Wagenmakers, E-J. (2011). Diffusion versus linear ballistic accumulation: different models but the same conclusions about psychological processes? Psychonomic Bulletin & Review, 18(1), 61-69. https://doi.org/10.3758/s13423-010-0022-4 [details]
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Dutilh, G., Krypotos, A-M., & Wagenmakers, E-J. (2011). Task-related versus stimulus-speciﬁc practice: a diffusion model account. Experimental Psychology, 58(6), 434-442. https://doi.org/10.1027/1618-3169/a000111 [details]

Dutilh, G., Wagenmakers, E-J., Visser, I., & van der Maas, H. L. J. (2011). A phase transition model for the speed-accuracy trade-off in response time experiments. Cognitive Science, 35(2), 211-250. https://doi.org/10.1111/j.1551-6709.2010.01147.x [details]

Forstmann, B. U., Tittgemeyer, M., Wagenmakers, E. J., Derrfuss, J., Imperati, D., & Brown, S. (2011). The speed-accuracy tradeoff in the elderly brain: a structural model-based approach. The Journal of Neuroscience, 31(47), 17242-17249. https://doi.org/10.1523/JNEUROSCI.0309-11.2011 [details]
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Forstmann, B. U., Wagenmakers, E-J., Eichele, T., Brown, S., & Serences, J. T. (2011). Reciprocal relations between cognitive neuroscience and formal cognitive models: opposites attract? Trends in Cognitive Sciences, 15(6), 272-279. https://doi.org/10.1016/j.tics.2011.04.002 [details]

Lodewyckx, T., Kim, W., Lee, M. D., Tuerlinckx, F., Kuppens, P., & Wagenmakers, E-J. (2011). A tutorial on Bayes factor estimation with the product space method. Journal of Mathematical Psychology, 55(5), 331-347. https://doi.org/10.1016/j.jmp.2011.06.001 [details]

Nieuwenhuis, S., Forstmann, B. U., & Wagenmakers, E-J. (2011). Erroneous analyses of interactions in neuroscience: a problem of significance. Nature Neuroscience, 14(9), 1105-1107. https://doi.org/10.1038/nn.2886 [details]

Nilsson, H., Rieskamp, J., & Wagenmakers, E-J. (2011). Hierarchical Bayesian parameter estimation for cumulative prospect theory. Journal of Mathematical Psychology, 55(1), 84-93. https://doi.org/10.1016/j.jmp.2010.08.006 [details]

Stringer, S., Borsboom, D., & Wagenmakers, E-J. (2011). Bayesian inference for the information gain model. Behavior Research Methods, 43(2), 297-309. https://doi.org/10.3758/s13428-010-0057-5 [details]
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Wagenmakers, E-J., Wetzels, R., Borsboom, D., & van der Maas, H. L. J. (2011). Why psychologists must change the way they analyze their data: the case of psi. Journal of Personality and Social Psychology, 100(3), 426-432. https://doi.org/10.1037/a0022790 [details]

Wetzels, R., Matzke, D., Lee, M. D., Rouder, J. N., Iverson, G. J., & Wagenmakers, E-J. (2011). Statistical evidence in experimental psychology: an empirical comparison using 855 t tests. Perspectives on Psychological Science, 6(3), 291-298. https://doi.org/10.1177/1745691611406923 [details]

van Maanen, L., Brown, S. D., Eichele, T., Wagenmakers, E-J., Ho, T., Serences, J., & Forstmann, B. U. (2011). Neural correlates of trial-to-trial fluctuations in response caution. The Journal of Neuroscience, 31(48), 17488-17495. https://doi.org/10.1523/JNEUROSCI.2924-11.2011 [details]

van Ravenzwaaij, D., Brown, S., & Wagenmakers, E-J. (2011). An integrated perspective on the relation between response speed and intelligence. Cognition, 119(3), 381-393. https://doi.org/10.1016/j.cognition.2011.02.002 [details]

van Ravenzwaaij, D., Dutilh, G., & Wagenmakers, E-J. (2011). Cognitive model decomposition of the BART: assessment and application. Journal of Mathematical Psychology, 55(1), 94-105. https://doi.org/10.1016/j.jmp.2010.08.010 [details]

van Ravenzwaaij, D., van der Maas, H. L. J., & Wagenmakers, E-J. (2011). Does the Name-Race Implicit Association Test measure racial prejudice? Experimental Psychology, 58(4), 271-277. https://doi.org/10.1027/1618-3169/a000093 [details]

2010

Bogacz, R., Wagenmakers, E. J., Forstmann, B. U., & Nieuwenhuis, S. (2010). The neural basis of the speed-accuracy tradeoff. Trends in Neurosciences, 33(1), 10-16. https://doi.org/10.1016/j.tins.2009.09.002 [details]

Forstmann, B. U., Anwander, A., Schäfer, A., Neumann, J., Brown, S., Wagenmakers, E. M., Bogacz, R., & Turner, R. (2010). Cortico-striatal connections predict control over speed and accuracy in perceptual decision making. Proceedings of the National Academy of Sciences of the United States of America, 107(36), 15916-15920. https://doi.org/10.1073/pnas.1004932107 [details]

Forstmann, B. U., Brown, S., Dutilh, G., Neumann, J., & Wagenmakers, E-J. (2010). The neural substrate of prior information in perceptual decision making: a model-based analysis. Frontiers in Human Neuroscience, 4, Article 40. https://doi.org/10.3389/fnhum.2010.00040 [details]
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Heathcote, A., Brown, S., Wagenmakers, E-J., & Eidels, A. (2010). Distribution-free tests of stochastic dominance for small samples. Journal of Mathematical Psychology, 54(5), 454-463. https://doi.org/10.1016/j.jmp.2010.06.005 [details]

Iverson, G. J., Lee, M. D., & Wagenmakers, E-J. (2010). The random effects prep continues to mispredict the probability of replication. Psychonomic Bulletin & Review, 17(2), 270-272. https://doi.org/10.3758/PBR.17.2.270 [details]

Iverson, G. J., Wagenmakers, E-J., & Lee, M. D. (2010). A model-averaging approach to replication: the case of prep. Psychological Methods, 15(2), 172-181. https://doi.org/10.1037/a0017182 [details]

Jepma, M., te Beek, E. T., Wagenmakers, E-J., van Gerven, J. M. A., & Nieuwenhuis, S. (2010). The role of the noradrenergic system in the exploration-exploitation trade-off: a psychopharmacological study. Frontiers in Human Neuroscience, 4, Article 170. https://doi.org/10.3389/fnhum.2010.00170 [details]
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Wagenmakers, E-J., Lodewyckx, T., Kuriyal, H., & Grasman, R. (2010). Bayesian hypothesis testing for psychologists: A tutorial on the Savage–Dickey method. Cognitive Psychology, 60(3), 158-189. https://doi.org/10.1016/j.cogpsych.2009.12.001 [details]

Wetzels, R., & Wagenmakers, E-J. (2010). Exemplary introduction to Bayesian statistical inference [Review of: I. Ntzoufras (2009) Bayesian modeling using WinBUGS]. Journal of Mathematical Psychology, 54(5), 466-469. https://doi.org/10.1016/j.jmp.2010.02.002 [details]

Wetzels, R., Grasman, R. P. P. P., & Wagenmakers, E-J. (2010). An encompassing prior generalization of the Savage-Dickey density ratio. Computational Statistics and Data Analysis, 54(9), 2094-2102. https://doi.org/10.1016/j.csda.2010.03.016 [details]

Wetzels, R., Lee, M. D., & Wagenmakers, E-J. (2010). Bayesian inference using WBDev: a tutorial for social scientists. Behavior Research Methods, 42(3), 884-897. https://doi.org/10.3758/BRM.42.3.884 [details]

Wetzels, R., Vandekerckhove, J., Tuerlinckx, F., & Wagenmakers, E-J. (2010). Bayesian parameter estimation in the Expectancy Valence model of the Iowa gamblling task. Journal of Mathematical Psychology, 54(1), 14-27. https://doi.org/10.1016/j.jmp.2008.12.001 [details]

2009

Dutilh, G., Vandekerckhove, J., Tuerlinckx, F., & Wagenmakers, E-J. (2009). A diffusion model decomposition of the practice effect. Psychonomic Bulletin & Review, 16(6), 1026-1036. https://doi.org/10.3758/16.6.1026 [details]

Grasman, R. P. P. P., Wagenmakers, E-J., & van der Maas, H. L. J. (2009). On the mean and variance of response times under the diffusion model with an application to parameter estimation. Journal of Mathematical Psychology, 53(2), 55-68. https://doi.org/10.1016/j.jmp.2009.01.006 [details]

Grasman, R. P. P. P., van der Maas, H. L. J., & Wagenmakers, E-J. (2009). Fitting the cusp catastrophe in R: a cusp-package primer. Journal of Statistical Software, 32(8), 1-28. http://www.jstatsoft.org/v32/i08/paper [details]
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Iverson, G. J., Lee, M. D., Zhang, S., & Wagenmakers, E-J. (2009). prep: an agony in five fits. Journal of Mathematical Psychology, 53(4), 195-202. https://doi.org/10.1016/j.jmp.2008.09.004 [details]

Iverson, G., Lee, M. D., & Wagenmakers, E-J. (2009). prep misestimates the probability of replication. Psychonomic Bulletin & Review, 16(2), 424-429. https://doi.org/10.3758/PBR.16.2.424 [details]

Jepma, M., Wagenmakers, E-J., Band, G. P. H., & Nieuwenhuis, S. (2009). The effects of accessory stimuli on information processing: evidence from electrophysiology and a diffusion model analysis. Journal of Cognitive Neuroscience, 21(5), 847-864. https://doi.org/10.1162/jocn.2009.21063 [details]
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Matzke, D., & Wagenmakers, E-J. (2009). Psychological interpretation of the ex-Gaussian and shifted Wald parameters: a diffusion model analysis. Psychonomic Bulletin & Review, 16(5), 798-817. https://doi.org/10.3758/PBR.16.5.798 [details]

Steyvers, M., Lee, M. D., & Wagenmakers, E-J. (2009). A Bayesian analysis of human decision-making on bandit problems. Journal of Mathematical Psychology, 53(3), 168-179. https://doi.org/10.1016/j.jmp.2008.11.002 [details]

Torre, K., & Wagenmakers, E-J. (2009). Theories and models for 1/fβ noise in human movement science. Human Movement Science, 28(3), 297-318. https://doi.org/10.1016/j.humov.2009.01.001 [details]

Wagenmakers, E-J. (2009). Methodological and empirical developments for the Ratcliff diffusion model of response times and accuracy. European Journal of Cognitive Psychology, 21(5), 641-671. https://doi.org/10.1080/09541440802205067 [details]

Wetzels, R., Raaijmakers, J. G. W., Jakab, E., & Wagenmakers, E-J. (2009). How to quantify support for and against the null hypothesis: a flexible winBUGS implementation of a default Bayesian t-test. Psychonomic Bulletin & Review, 16(4), 752-760. https://doi.org/10.3758/PBR.16.4.752 [details]

2008

Ahn, W-Y., Busemeyer, J. R., Wagenmakers, E-J., & Stout, J. C. (2008). Comparison of decision learning models using the generalization criterion method. Cognitive Science, 32, 1376-1402. https://doi.org/10.1080/03640210802352992 [details]

Forstmann, B. U., Dutilh, G., Brown, S., Neumann, J., von Cramon, D. Y., Ridderinkhof, K. R., & Wagenmakers, E-J. (2008). Striatum and pre-SMA facilitate decision-making under time pressure. Proceedings of the National Academy of Sciences of the United States of America, 105(45), 17538-17542. https://doi.org/10.1073/pnas.0805903105 [details]

Shiffrin, R. M., Lee, M. D., Kim, W., & Wagenmakers, E-J. (2008). A survey of model evaluation approaches with a tutorial on hierarchical Bayesian methods. Cognitive Science, 32, 1248-1284. https://doi.org/10.1080/03640210802414826 [details]

Wagenmakers, E-J., Ratcliff, R., Gomez, P., & McKoon, G. (2008). A diffusion model account of criterion shifts in the lexical decision task. Journal of Memory and Language, 58(1), 140-159. https://doi.org/10.1016/j.jml.2007.04.006 [details]

Wagenmakers, E-J., van der Maas, H. L. J., Dolan, C. V., & Grasman, R. P. P. P. (2008). EZ does it! Extensions of the EZ-diffusion model. Psychonomic Bulletin & Review, 15, 1229-1235. https://doi.org/10.3758/PBR.15.6.1229 [details]
2023

Aczel, B., & Wagenmakers, E. M. (2023). Transparency Guidance for ChatGPT Usage in Scientific Writing. (pp. 1-6). PsyArXiv. https://doi.org/10.31234/osf.io/b58ex

Bartoš, F., Maier, M., Stanley, T. D., & Wagenmakers, E. M. (2023). Robust Bayesian Meta-Regression — Model-Averaged Moderation Analysis in the Presence of Publication Bias. (pp. 1-34). PsyArXiv. https://doi.org/10.31234/osf.io/98xb5

Bartoš, F., Otte, W. M., Gronau, Q. F., Timmers, B., Ly, A., & Wagenmakers, E. M. (2023). Empirical prior distributions for Bayesian meta-analyses of binary and time to event outcomes. (pp. 1-23). ArXiv. https://doi.org/10.48550/arXiv.2306.11468

Bartoš, F., Sarafoglou, A. S. G., Godmann, H. R., Sahrani, A., Klein Leunk, D., Gui, P. Y., Voss, D., Ullah, K., Zoubek, M. J., Nippold, F., Aust, F., Vieira, F. F., Islam, C.-G., Zoubek, A. J., Shabani, S., Petter, J., Roos, I. B., Finnemann, A. T. K., Lob, A. B., ... Wagenmakers, E. M. (2023). Fair coins tend to land on the same side they started: Evidence from 350,757 flips. (pp. 1-12). ArXiv. https://doi.org/10.48550/arXiv.2310.04153

Bartoš, F., Wagenmakers, E. M., Vinkers, C. H., Braun, K. P. J., & Otte, W. M. (2023). Contextual aggregation and rapid updating of trial outcomes within a user-friendly open-source environment. (pp. 1-10). ArXiv. https://doi.org/10.48550/arXiv.2306.14061

Kucharský, S., & Wagenmakers, E. M. (2023). Correct Conclusions from Fallible Medical Tests: A Tutorial with JASP. (pp. 1-24). OSF Preprints. https://doi.org/10.31219/osf.io/jksz6

Kucharský, S., Wagenmakers, E. M., van den Bergh, D., & Ly, A. (2023). Analytic Posterior Distribution and Bayes Factor for Pearson Partial Correlations. (pp. 1-32). PsyArXiv. https://doi.org/10.31234/osf.io/6muwy

Maier, M., Bartoš, F., Raihani, N., Shanks, D., Stanley, T. D., Wagenmakers, E. M., & Harris, A. (2023). Exploring Open Science Practices in Behavioural Public Policy Research. (pp. 1-12). PsyArXiv. https://doi.org/10.31234/osf.io/msv8y

Wagenmakers, E. M., Godmann, H. R., de Ruiter, J. P. A., & van Doorn, J. B. (2023). Visualizing the Equation for the Sample Correlation Coefficient. (pp. 1-8). PsyArXiv. https://doi.org/10.31234/osf.io/gwu8b

Wagenmakers, E. M., Kucharský, S., van Doorn, J. B., & van den Bergh, D. (2023). Accessible and Sustainable Statistics with JASP. (pp. 1-12). PsyArXiv. https://doi.org/10.31234/osf.io/ud2vj

van Doorn, J., Aust, F., Haaf, J. M., Stefan, A. M., & Wagenmakers, E.-J. (2023). Bayes Factors for Mixed Models: Perspective on Responses. Computational Brain and Behavior, 6(1), 127–139. https://doi.org/10.1007/s42113-022-00158-x [details]
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van Doorn, J., Haaf, J. M., Stefan, A. M., Wagenmakers, E.-J., Cox, G. E., Davis-Stober, C. P., Heathcote, A., Heck, D. W., Kalish, M., Kellen, D., Matzke, D., Morey, R. D., Nicenboim, B., van Ravenzwaaij, D., Rouder, J. N., Schad, D. J., Shiffrin, R. M., Singmann, H., Vasishth, S., ... Aust, F. (2023). Bayes Factors for Mixed Models: a Discussion. Computational Brain and Behavior, 6(1), 140–158. https://doi.org/10.1007/s42113-022-00160-3 [details]
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2022

Bartoš, F., Maier, M., Stanley, T. D., & Wagenmakers, E. M. (2022). Adjusting for Publication Bias Reveals Mixed Evidence for the Impact of Cash Transfers on Subjective Well-Being and Mental Health. (pp. 1-7). PsyArXiv. https://doi.org/10.31234/osf.io/d9vcg

Bartoš, F., Pawel, S., & Wagenmakers, E. M. (2022). When Evidence and Significance Collide. (pp. 1-3). ArXiv. https://doi.org/10.48550/arXiv.2206.04435

Derks, K., de Swart, J., Wagenmakers, E. M., & Wetzels, R. (2022). An impartial Bayesian hypothesis test for audit sampling. (pp. 1-35). PsyArXiv. https://doi.org/10.31234/osf.io/8nf3e

Maier, M., Bartoš, F., Oh, M., Wagenmakers, E. M., Shanks, D., & Harris, A. (2022). Adjusting for Publication Bias Reveals That Evidence for and Size of Construal Level Theory Effects is Substantially Overestimated. (pp. 1-40). PsyArXiv. https://doi.org/10.31234/osf.io/r8nyu

Maier, M., Bartoš, F., Quintana, D., Dablander, F., van den Bergh, D., Marsman, M., Ly, A., & Wagenmakers, E. M. (2022). Model-Averaged Bayesian t-Tests. (pp. 1-44). PsyArXiv. https://doi.org/10.31234/osf.io/d5zwc

Maier, M., Bartoš, F., Stanley, T. D., Shanks, D. R., Harris, A. J. L., & Wagenmakers, E-J. (2022). No evidence for nudging after adjusting for publication bias. Proceedings of the National Academy of Sciences of the United States of America, 119(31), Article e2200300119. Advance online publication. https://doi.org/10.1073/pnas.2200300119 [details]
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Wagenmakers, E-J., Sarafoglou, A., & Aczel, B. (2022). One statistical analysis must not rule them all. Nature, 605(7910), 423-425. Advance online publication. https://doi.org/10.1038/d41586-022-01332-8 [details]

Wagenmakers, E. M. (2022). Approximate Objective Bayes Factors From P-Values and Sample Size: The 3p√n Rule. (pp. 1-50). PsyArXiv. https://doi.org/10.31234/osf.io/egydq

Wagenmakers, E. M., & Gronau, Q. F. (2022). Evidence of Absence in the D-HEALTH Trial: A Bayesian Reanalysis. (pp. 1-5). PsyArXiv. https://doi.org/10.31234/osf.io/t3m2c

van Ravenzwaaij, D., & Wagenmakers, E-J. (2022). Advantages Masquerading as “Issues” in Bayesian Hypothesis Testing: A Commentary on Tendeiro and Kiers (2019). Psychological Methods, 27(3), 451-465. Advance online publication. https://doi.org/10.1037/met0000415 [details]

2021

Shiffrin, R. M., Matzke, D., Crystal, J. D., Wagenmakers, E-J., Chandramouli, S. H., Vandekerckhove, J., Zorzi, M., Morey, R. D., & Murphy, M. C. (2021). Extraordinary claims, extraordinary evidence? A discussion. Learning and Behavior, 49(3), 265-275. Advance online publication. https://doi.org/10.3758/s13420-021-00474-5 [details]
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Verschuere, B., De Schryver, M., van den Bergh, D., Wagenmakers, E.-J., & Meijer, E. (2021). Are dishonest politicians more likely to be reelected? A Bayesian view. Proceedings of the National Academy of Sciences of the United States of America, 118(6), Article e2022718118. https://doi.org/10.1073/pnas.2022718118 [details]
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Wagenmakers, E. J. (2021). Defiant Denial is Self-Defeating. Psychological Inquiry, 32(1), 12-16. https://doi.org/10.1080/1047840X.2021.1889314 [details]

Wagenmakers, E. M., & Gronau, Q. F. (2021). A Bayesian Analysis of the Molnupiravir Trial Data. (pp. 1-5). PsyArXiv. https://doi.org/10.31234/osf.io/m4a95

van Doorn, J., & Wagenmakers, E-J. (2021). Strong public claims may not reflect researchers' private convictions. Significance, 18(1), 44-45. https://doi.org/10.1111/1740-9713.01493 [details]

2020

Aczel, B., Hoekstra, R., Gelman, A., Wagenmakers, E-J., Klugkist, I. G., Rouder, J. N., Vandekerckhove, J., Lee, M. D., Morey, R. D., Vanpaemel, W., Dienes, Z., & van Ravenzwaaij, D. (2020). Discussion points for Bayesian inference. Nature Human Behaviour, 4(6), 561–563. Advance online publication. https://doi.org/10.1038/s41562-019-0807-z [details]

Aczel, B., Szaszi, B., Sarafoglou, A., Kekecs, Z., Kucharský, Š., Benjamin, D., Chambers, C. D., Fisher, A., Gelman, A., Gernsbacher, M. A., Ioannidis, J. P., Johnson, E., Jonas, K., Kousta, S., Lilienfeld, S. O., Lindsay, D. S., Morey, C. C., Munafò, M., Newell, B. R., ... Wagenmakers, E-J. (2020). A consensus-based transparency checklist. Nature Human Behaviour, 4(1), 4-6. Advance online publication. https://doi.org/10.1038/s41562-019-0772-6 [details]
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s41562-019-0772-6
Supplementary files
41562 2019 772 MOESM1 ESM

Forscher, P. S., Wagenmakers, E. M., Coles, N. A., Silan, M. A., Dutra, N., Basnight-Brown, D., & IJzerman, H. (2020). A Manifesto for Big Team Science. (PsyArXiv). https://doi.org/10.31234/osf.io/2mdxh

Gronau, Q. F., & Wagenmakers, E. M. (2020). Hydroxychloroquine in Patients with COVID-19 (Chen et al., 2020): Absence of Evidence, Not Evidence of Absence. (pp. 1-3). PsyArXiv. https://doi.org/10.31234/osf.io/rqhgj

Haaf, J. M., Hoogeveen, S., Berkhout, S., Gronau, Q. F., & Wagenmakers, E. M. (2020). A Bayesian Multiverse Analysis of Many Labs 4: Quantifying the Evidence against Mortality Salience. (v1 ed.) PsyArXiv. https://doi.org/10.31234/osf.io/cb9er

Heck, D. W., Böhm, U., Böing-Messing, F., Bürkner, P-C., Derks, K., Dienes, Z., Fu, Q., Gu, X., Karimova, D., Kiers, H. A. L., Klugkist, I., Kuiper, R., Lee, M. D., Leenders, R., Leplaa, H. J., Linde, M., Ly, A., Meijerink-Bosman, M., Moerbeek, M., ... Hoijtink, H. (2020). A review of applications of the Bayes factor in psychological research. (PsyArXiv). https://doi.org/10.31234/osf.io/cu43g

Hulme, O. J., Wagenmakers, E. M., Damkier, P., Madelung, C. F., Siebner, H. R., Helweg-Larsen, J., Gronau, Q. F., Benfield, T., & Madsen, K. H. (2020). Reply to Gautret et al. 2020: A Bayesian reanalysis of the effects of hydroxychloroquine and azithromycin on viral carriage in patients with COVID-19. medRxiv. https://doi.org/10.1101/2020.03.31.20048777

Hutton, J. L., Diggle, P. J., Bird, S. M., Hennig, C., Longford, N., Mathur, M. B., Vander Weele, T. J., Ioannidis, J. P. A., Chai, C. P., Dowe, D. L., Ferguson, J., Fitz-Simon, N., Friede, T., Rover, C., Grieve, A. P., Kumar, K., Ly, A., Mansmann, U., Mateu, J., ... Held, L. (2020). Discussion on the meeting on ‘Signs and sizes: understanding and replicating statistical findings’. Journal of the Royal Statistical Society. Series A (Statistics in Society), 183(2), 449-469. Advance online publication. https://doi.org/10.1111/rssa.12544 [details]

Wagenmakers, E-J. (2020). Statistical dark arts endanger democracy — and life: Two scourges of the infodemic show how to spot quantitative chicanery. [Review of: C.T. Bergstrom, J.D. West (2020) Calling Bullshit: The Art of Scepticism in a Data‑Driven World]. Nature, 584(7819), 36. https://doi.org/10.1038/d41586-020-02280-x [details]

Wagenmakers, E. M., & Gronau, Q. F. (2020). Absence of Evidence and Evidence of Absence in the FLASH Trial: A Bayesian Reanalysis. (pp. 1-3). PsyArXiv. https://doi.org/10.31234/osf.io/4pf9j

Wagenmakers, E. M., & Gronau, Q. F. (2020). Efficacy of Hydroxychloroquine in Patients with COVID-19 (Chen et al., 2020): Moderate Evidence for a Treatment Effect on Pneumonia. (pp. 1-3). PsyArXiv. https://doi.org/10.31234/osf.io/7nk8z

Wagenmakers, E. M., & Ly, A. (2020). Bayesian Scepsis About SWEPIS: Quantifying the Evidence That Early Induction of Labour Prevents Perinatal Deaths. (pp. 1-5). PsyArXiv. https://doi.org/10.31234/osf.io/5ydpb

Wagenmakers, E.-J., & Gronau, Q. F. (2020). Overwhelming Evidence for Vaccine Efficacy in the Pfizer Trial: An Interim Bayesian Analysis. PsyArXiv. https://doi.org/10.31234/osf.io/fs562

2019

Evans, N. J., Tillman, G., & Wagenmakers, E-J. (2019). Systematic and random sources of variability in perceptual decision-making: Comment on Ratcliff, Voskuilen, and McKoon (2018). (v1 ed.) PsyArXiv. https://doi.org/10.31234/osf.io/j98qd [details]
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Systematic and Random Sources of Variability in Perceptual Decision Making Comment on Ratcliff Voskuilen and McKoon 2019 06 17T12 15 06.428Z version 1
Systematic and Random Sources of Variability in Perceptual Decision Making Comment on Ratcliff Voskuilen and McKoon

Gronau, Q. F., & Wagenmakers, E. M. (2019). Progesterone in Women with Bleeding in Early Pregnancy: Absence of Evidence: Not Evidence of Absence: Not Evidence of Absence. (pp. 1-2). PsyArXiv. https://doi.org/10.31234/osf.io/etk7g

Gronau, Q. F., Wagenmakers, E. J., Heck, D. W., & Matzke, D. (2019). Erratum to: A Simple Method for Comparing Complex Models: Bayesian Model Comparison for Hierarchical Multinomial Processing Tree Models Using Warp-III Bridge Sampling. Psychometrika, 84(4), 1047. https://doi.org/10.1007/s11336-019-09681-6

Haaf, J. M., Ly, A., & Wagenmakers, E-J. (2019). Retire significance, but still test hypotheses. Nature, 567(7749), 461. https://doi.org/10.1038/d41586-019-00972-7 [details]
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Sampaio, C., Ware, J. J., Macleod, M., Wagenmakers, E. J., & Munafò, M. (2019). Reader response: Evaluating depression and suicidality in tetrabenazine users with Huntington disease. Neurology, 92(9), 447-448. https://doi.org/10.1212/WNL.0000000000006999

Wagenmakers, E. M., Gronau, Q. F., & Vandekerckhove, J. (2019). Five Bayesian Intuitions for the Stopping Rule Principle. PsyArXiv. https://doi.org/10.31234/osf.io/5ntkd

2018

Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E. J., Berk, R., Bollen, K. A., Brembs, B., Brown, L., Camerer, C., Cesarini, D., Chambers, C. D., Clyde, M., Cook, T. D., De Boeck, P., Dienes, Z., Dreber, A., Easwaran, K., Efferson, C., ... Johnson, V. E. (2018). Redefine statistical significance. Nature Human Behaviour, 2(1), 6-10. https://doi.org/10.1038/s41562-017-0189-z

2017

Keuken, M. C., Ly, A., Boekel, W., Wagenmakers, E-M., Belay, L., Verhagen, J., Brown, S. D., & Forstmann, B. U. (2017). Corrigendum to “A purely confirmatory replication study of structural brain-behavior correlations” [Cortex 66 (2015) 115–133]. Cortex, 93, 229-233. Advance online publication. https://doi.org/10.1016/j.cortex.2017.03.007 [details]

Wagenmakers, E. M., Marsman, M., van den Bergh, D., Chambers, C., Pashler, H., de Ruiter, J. P., Fischer, A., Giner-Sorolla, R., Inzlicht, M., Jonas, K. J., Cesario, J., Borsboom, D., van der Maas, H., Harris, C., Freitas, A., Vazire, S., Gervais, W., Milyavskaya, M., Dunn, E. W., ... Tullett, A. (2017). Suggestions to Advance Your Mission: An Open Letter to Dr. Shinobu Kitayama, Editor of JPSP:ASC. PsyArXiv. https://doi.org/10.31234/osf.io/39ugj

2016

Marsman, M., Ly, A., & Wagenmakers, E-J. (2016). Four Requirements for an Acceptable Research Program. Basic and Applied Social Psychology, 38(6), 308-312. https://doi.org/10.1080/01973533.2016.1221349 [details]

Morey, R. D., Hoekstra, R., Rouder, J. N., & Wagenmakers, E-J. (2016). Continued misinterpretation of confidence intervals: Response to Miller and Ulrich. Psychonomic Bulletin & Review, 23(1), 131-140. Advance online publication. https://doi.org/10.3758/s13423-015-0955-8 [details]
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2015

Forstmann, B. U., & Wagenmakers, E-J. (2015). An introduction to model-based cognitive neuroscience. Springer. https://doi.org/10.1007/978-1-4939-2236-9 [details]

2013

Bakker, M., Cramer, A. O. J., Matzke, D., Kievit, R. A., van der Maas, H. L. J., Wagenmakers, E-J., & Borsboom, D. (2013). Dwelling on the past. European Journal of Personality, 27(2), 120-144. Advance online publication. https://doi.org/10.1002/per.1920 [details]

Bakker, M., Wagenmakers, E-J., Borsboom, D., Wicherts, J., & van der Maas, H. (2013). Spelregels in de psychologie: over eerlijk en goed onderzoek. De Psycholoog, 48(12), 68-76. [details]

Wagenmakers, E-J. (2013). Sjoemelwetenschap. De Psycholoog, 48(4), 34-35. http://www.psynip.nl/website-openbaar-de-psycholoog/psy1304_forum-hofstee.pdf [details]

2011

Borsboom, D., Wagenmakers, E-J., & Romeijn, J-W. (2011). Mechanistic curiosity will not kill the Bayesian cat. Behavioral and Brain Sciences, 34(4), 192-193. https://doi.org/10.1017/S0140525X11000215 [details]

Wagenmakers, E-J. (2011). Kleren voor de keizer [Bespreking van: R. van de Schoot (2010) Informative hypotheses: how to move beyond classical null hypothesis testing]. De Psycholoog, 46(1), 21-22. [details]

2009

Wagenmakers, E-J. (2009). How do individuals reason in the Wason card selection task [Review of: M. Oaksford, N. Chater (2007) Bayesian rationality: the probabilistic approach to human reasoning]. Behavioral and Brain Sciences, 32(1), 104-104. https://doi.org/10.1017/S0140525X09000508 [details]

2008

Wagenmakers, E-J., Lee, M. D., Lodewyckx, T., & Iverson, G. (2008). Bayesian versus frequentist inference. In H. Hoijtink, I. Klugkist, & P. A. Boelen (Eds.), Bayesian evaluation of informative hypotheses (pp. 181-207). (Statistics for Social and Behavioral Sciences). Springer. https://doi.org/10.1007/978-0-387-09612-4_9 [details]
2021

Ly, A., van den Bergh, D., Bartoš, F., & Wagenmakers, E-J. (2021). Bayesian inference with JASP. ISBA Bulletin, 28(1), 7-15. https://bayesian.org/wp-content/uploads/2021/03/2103.pdf [details]

Wagenmakers, E-M. (2021). [Review of: A. Clayton (2021) Bernoulli’s Fallacy : Statistical Illogic and the Crisis of Modern Science]. CHANCE, 34(4), 37-38. Advance online publication. https://doi.org/10.1080/09332480.2021.2003642 [details]

2019

Wagenmakers, E-J. (2019). Het belang van Brady versus Maryland voor de psychologie. De Psycholoog, 54(12), 24-28. https://osf.io/6w4zn/ [details]

Wagenmakers, E-J. (2019). Het plagiaat van Lord Francis Bacon. Skepter, 32(2), 43-46. https://skepsis.nl/bacon/ [details]

Wagenmakers, E-J. (2019). Prins op een missie: [Boekbespreking van: C. Chambers (2018) De 7 doodzonden van de psychologie: pleidooi voor een cultuuromslag in de wetenschappelijke praktijk]. De Psycholoog, 54(3), 28-29. https://osf.io/uvw83/ [details]

2016

Wagenmakers, E-J. (2016). [Review of: R.B. Kline (2013) Beyond significance testing: Statistics reform in the behavioral sciences]. American Statistician, 70(2), 221. https://doi.org/10.1080/00031305.2016.1185863 [details]

Wagenmakers, E-J., & Dutilh, G. (2016). Preregistration: Why, what, where? Psychology Research Institute of the University of Amsterdam. [details]
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2013

Borsboom, D., & Wagenmakers, E-J. (2013). Derailed: the rise and fall of Diederik Stapel [Review of: D. Stapel (2012) Ontsporing]. APS Observer, 26(1). http://www.psychologicalscience.org/index.php/publications/observer/2013/january-13/derailed-the-rise-and-fall-of-diederik-stapel.html [details]
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2009

Wagenmakers, E-J. (2009). Teaching graduate students how to write clearly. APS Observer, 22(4). http://www.psychologicalscience.org/observer/getArticle.cfm?id=2499 [details]
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2008

Wagenmakers, E-J., & van der Maas, H. (2008). [Review of: A.R. Jensen (2006) Clocking the mind: mental chronometry and individual differences]. Intelligence, 36(5), 493-494. https://doi.org/10.1016/j.intell.2007.09.001 [details]
2021

Wagenmakers, E. M. (2021). De grote SKEPTER-skepsistest. Skepter, 34(3), 4-8. https://skepsis.nl/skepter-covers/skepter-34-3-2021/#

2020

Wagenmakers, E. M. (2020). Bayesian Thinking for Toddlers. JASP. https://doi.org/10.31234/osf.io/w5vbp

Wagenmakers, E. M., & Pecher, D. (2020). KoppenEnStaarten2020. Skepter, 33(4), 16-20.

2017

Wagenmakers, E. M. (2017). Het zwaard van Alhazen. Skepter, 30, 34-35.

2011

Borsboom, D., Wagenmakers, E-J., Kievit, R. A., Wetzels, R., van den Berg, H., & Wicherts, J. M. (2011). Universiteiten en subsidieverstrekkers moeten fraude aanpakken. De Volkskrant.

Kievit, R. A., Borsboom, D., Wagenmakers, E-J., Wicherts, J. M., Wetzels, R., van Harmelen, A-L., & van den Berg, H. (2011). Maatregel om fraude te bemoeilijken brengt enkel voordelen met zich mee. De Volkskrant.
2017

Ly, A., Raj, A., Wagenmakers, E. M., & Marsman, M. (2017). A limit-consistent Bayes factor for testing the equality of two Poisson rates. Poster session presented at International Workshop on Objective Bayes Methodology, Austin, United States.

2015

Ly, A., Marsman, M., & Wagenmakers, E-J. (2015). Jeffrey's Correlation Test Based on Criteria of Bayarri, Berger, Forte, and Garcia-Donato (2012). Poster session presented at 11th International Workshop on Objective Bayes Methodology.

Ly, A., Marsman, M., & Wagenmakers, E. M. (2015). Jeffreys’s Correlation Test Based on Criteria of Bayarri, Berger, Forte, and Garcia-Donato (2012). Poster session presented at Objective Bayesian Analysis, Valencia, Spain.
Prize / grant

Wagenmakers, E. M. (2018). Verbindingsprijs.

Wagenmakers, E. M. & Stefan, A. M. (2018). MaGW research talent (NWO).

Wagenmakers, E. M. & Kucharsky, S. (2018). MaGW research talent (NWO).

Wagenmakers, E. M. (2017). Advanced Grant from the European Research Council (ERC).

Wagenmakers, E. M. (2017). VICI grant from the Netherlands Organisation for Scientific Research (NWO).

Wagenmakers, E. M. (2017). PhD grant from NWO.

Wagenmakers, E.-J. (2013). Dynamic adjustment of response caution in perceptual decision-making..

Wagenmakers, E.-J. (2012). Partner investigator on the Australian Research Council three-year project "Rapid Decisions: From Neuroscience to Complex Cognitions".

Wagenmakers, E.-J. (2012). Partner investigator on the Australian Research Council three-year project "Cognitive Flexibility from Adolescence to Senescence: Variability Associated with Cognitive Strategy and Brain Connectivity"..

Wagenmakers, E.-J. (2012). Inaugural recipient of the Newcastle Psychology Research Visitor Fellowship..

Membership / relevant position

Wagenmakers, E. M. (2017). Member of the committee on Replication Research (“Replicatieonderzoek”) organized by the Royal Netherlands Academy of Arts and Sciences (KNAW), KNAW.

Wagenmakers, E. M. (2017). Member of Advisory Board, PsychFileDrawer.org project.

Wagenmakers, E. M. (2016-2017). Member of the committee on Replication Research (“Replicatieonderzoek”) organized by the Royal Netherlands Academy of Arts and Sciences (KNAW), (…), KNAW.

Wagenmakers, E.-J. (2010). Keynote: Bayesian model selection in sensometrics., the 10th Conference on Sensometrics, Rotterdam, the Netherlands, July 2010..

Wagenmakers, E.-J. (2010). Subsidie: The "ALW open competition" postdoc project "The neural basis of decision-making with multiple choice alternatives" was awarded a three-year (…), Netherlands Organisation for Scientific Research (NWO).

Journal editor

Wagenmakers, E.-J. (editor) (2015). Psychonomic Bulletin & Review (Journal).

Wagenmakers, E.-J. (editor) (2010). Cognitive Psychology (Journal).

Wagenmakers, E.-J. (editor) (2010). Journal of Mathematical Psychology (Journal).

Wagenmakers, E.-J. (editor) (2010). Psychonomic Bulletin & Review (Journal).

Talk / presentation

Wagenmakers, E. M. (speaker) (15-10-2018). Bayesian inference without tears, Centre International de Rencontres Mathematiques (CIRM).

Wagenmakers, E. M. (speaker) (1-9-2018). Bayesian advantages for the pragmatic researcher, Kongress der Deutschen Gesellschaft für Psychologie, Frankfurt.

Wagenmakers, E. M. (speaker) (30-4-2018). Tip of the iceberg? Revealing hidden uncertainty in cognitive modeling, h-MPT Network Meeting, Mannheim.

Wagenmakers, E. M. (speaker) (20-4-2018). Bayesian inference with JASP, Netherlands Institute for Neuroscience NIN - KNAW.

Wagenmakers, E. M. (speaker) (10-4-2018). The case for radical transparency in statistical reporting, University of Utrecht, Utrecht.

Wagenmakers, E. M. (speaker) (1-4-2018). Bayesian statistics using JASP, VU, Amsterdam.

Wagenmakers, E. M. (speaker) (20-1-2018). The case for radical transparency in statistical reporting., Replication and Reproducibility Event II: Moving Psychological Science Forward , Londen.

Wagenmakers, E. M. (speaker) (12-2017). Barbecue chicken alert!, BITTS.

Wagenmakers, E. M. (speaker) (11-2017). An introduction to JASP, Graduate School Neurosciences Amsterdam (ONWAR) .

Wagenmakers, E. M. (speaker) (11-2017). Hidden pseudoscience: Ailment, diagnosis, and cure, Amsterdam Skeptics in the Pub.

Wagenmakers, E. M. (speaker) (10-2017). The case for radical transparency in statistical reporting, ASA, American Sociological Association.

Wagenmakers, E. M. (speaker) (10-2017). The why and how of testing a point-null hypothesis within a Bayesian framework, TU Delft.

Wagenmakers, E. M. (speaker) (10-2017). Redefine statistical significance with JASP, IMC.

Wagenmakers, E. M. (speaker) (9-2017). JASP/Evidence, BITTS.

Wagenmakers, E. M. (speaker) (9-2017). “JASP Training Course”, 20th Conference of the European Society for Cognitive Psychology (ESCoP).

Wagenmakers, E. M. (speaker) (9-2017). Bayesian statistics without tears, Oxford University.

Wagenmakers, E. M. (speaker) (6-2017). The maximum diagnosticity of the p-value, workshop “Is there a future without null hypothesis significance testing?”.

Wagenmakers, E. M. (speaker) (6-2017). History and statistical foundation of preregistration, Tilburg University.

Wagenmakers, E. M. (speaker) (5-2017). “Bayesian Inference with JASP: A Fresh Way to Do Statistics", 29th Annual Convention of the Association for Psychological Science.

Wagenmakers, E. M. (speaker) (4-2017). “JASP: A Fresh Way to do Statistics”, BBSRC STARS Course “Advanced Methods for Reproducible Science”.

Wagenmakers, E. M. (speaker) (3-2017). “Bayesian Inference in Theory and Practice: A JASP Workshop”, Philips Research.

Wagenmakers, E. M. (speaker) (2-2017). “A personal perspective on the analysis of neuroscience data”, 6th Berlin Winter School on Ethics and Neuroscience.

Wagenmakers, E. M. (speaker) (2017). The methodological metamorphosis of neuroscience, 6th Berlin Winter School on Ethics and Neuroscience.

Wagenmakers, E. M. (speaker) (2017). KNAW report: Replication studies, NAS.

Wagenmakers, E. M. (speaker) (2017). “Bayesian analysis with JASP: A fresh way to do statistics”, Max Planck School for Language Sciences.

Others

van Doorn, J. (organiser), Wagenmakers, E.-J. (organiser), Matzke, D. (organiser), Ly, A. (organiser) & Sarafoglou, A. (organiser) (26-8-2019 - 30-8-2019). Ninth Annual JAGS and WinBUGS Workshop: Bayesian Modeling for Cognitive Science (organising a conference, workshop, ...).

van Doorn, J. (organiser), Wagenmakers, E.-J. (organiser), Sarafoglou, A. (organiser) & Morey, R. D. (organiser) (22-8-2019 - 23-8-2019). Theory and Practice of Bayesian Hypothesis Testing (organising a conference, workshop, ...).

Matzke, D. (organiser), Wagenmakers, E.-J. (organiser) & Tuerlinckx, F. (organiser) (25-3-2019 - 29-3-2019). Erasmus Seminar on Mathematical Psychology: “Formal Models and Quantitative Methods for Psychology” (organising a conference, workshop, ...).

Wagenmakers, E. M. (organiser), Matzke, D. (organiser), Lee, M. (organiser), Ly, A. (organiser), van Doorn, J. B. (organiser) & Gronau, Q. F. (organiser) (20-8-2018 - 24-8-2018). Eight Annual JAGS and WinBUGS Workshop: Bayesian Modeling for Cognitive Science (organising a conference, workshop, ...).

Wagenmakers, E. M. (organiser), Gronau, Q. F. (organiser), Ly, A. (organiser), van Doorn, J. B. (organiser) & Matzke, D. (organiser) (28-8-2017 - 29-8-2017). Theory and Practice of Bayesian Hypothesis Testing: A JASP Workshop (organising a conference, workshop, ...). http://(https://jasp- stats.org/upcoming-events/jasp-workshop/

Wagenmakers, E. M. (organiser), Ly, A. (organiser), Gronau, Q. F. (organiser), van Doorn, J. B. (organiser), Matzke, D. (organiser) & Lee, M. (organiser) (21-8-2017 - 25-8-2017). Seventh Annual JAGS and WinBUGS Workshop: Bayesian Modeling for Cognitive Science (organising a conference, workshop, ...). http://bayescourse.socsci.uva.nl/index.php?src=hom e

Wagenmakers, E. M. (participant) (2017). Fellow for the Association for Psychological Science (other).

Wagenmakers, E. M. (consultant) (2017). Statistical consulting, CHDI Foundation (consultancy).

Wagenmakers, E. M. (organiser), Matzke, D. (organiser), Selker, R. (organiser), van Doorn, J. B. (organiser) & Ly, A. (organiser) (2016). Theory and Practice of Bayesian Hypothesis Testing: A JASP Workshop (organising a conference, workshop, ...).

Wagenmakers, E. M. (organiser), Matzke, D. (organiser), Selker, R. (organiser), van Doorn, J. B. (organiser), Steingröver, H. M. (organiser), Lee, M. (organiser) & Ly, A. (organiser) (2016). Sixth Annual JAGS and WinBUGS Workshop: Bayesian Modeling for Cognitive Science (organising a conference, workshop, ...).

Wagenmakers, E.-J. (organiser), Tuerlinckx, F. (organiser) & Matzke, D. (organiser) (22-3-2015 - 28-3-2015). Erasmus-IP Seminar on Mathematical Psychology, Debrecen. Formal Models and Quantitative Methods for Psychology. (organising a conference, workshop, ...).

Wagenmakers, E.-J. (organiser), Matzke, D. (organiser) & Ly, A. (organiser) (2015). First Annual JASP Workhop: A Fresh Way to do Bayesian Statistics., Amsterdam (organising a conference, workshop, ...).

Wagenmakers, E.-J. (organiser), Lee, M. D. (organiser), Ly, A. (organiser) & Matzke, D. (organiser) (2015). Fifth Annual WinBUGS Workshop: Bayesian Modeling for Cognitive Science., Amsterdam (organising a conference, workshop, ...).

Wagenmakers, E.-J. (organiser), Lee, M. D. (organiser), Ly, A. (organiser), Matzke, D. (organiser), Steingroever, H. (organiser) & Verhagen, A. J. (organiser) (11-8-2014 - 15-8-2014). Fourth Annual WinBUGS Workshop: Bayesian Modeling for Cognitive Science., Amsterdam (organising a conference, workshop, ...).

Wagenmakers, E.-J. (organiser), Matzke, D. (organiser), Steingröver, H. M. (organiser) & Ly, A. (organiser) (12-8-2013 - 16-8-2013). WinBUGS Workshop: Bayesian Modeling for Cognitive Science., Amsterdam (organising a conference, workshop, ...).

Wagenmakers, E.-J. (organiser), Matzke, D. (organiser), Steingröver, H. M. (organiser) & Lee, M. (organiser) (2-7-2012 - 6-7-2012). Organisation of the workshop "Bayesian Modeling for Cognitive Science"., Amsterdam (organising a conference, workshop, ...).

Wagenmakers, E.-J. (organiser) & Forstmann, B. U. (organiser) (2012). Organisation of the Academy Colloquium "New Insights from Model-Based Cognitive Neuroscience", Amsterdam (organising a conference, workshop, ...).

Wagenmakers, E. M. (organiser), Wetzels, R. M. (organiser), Matzke, D. (organiser) & Lee, M. (organiser) (22-8-2011). Bayesian Modeling for Cognitive Science (organising a conference, workshop, ...).
2017

Steingröver, H. M. (2017). Safe models for risky decisions. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
Downloads
Thesis (complete)
Front matter
1. Introduction
2. Performance of healthy participants on the Iowa gambling task
3. A comparison of reinforcement-learning models for the Iowa gambling task using parameter space partitioning
4. Validating the PVL-Delta model for the Iowa gambling task
5. Absolute performance of reinforcement-learning models for the Iowa gambling task
6. ŵ = .2, â = .8, ĉ = .6: So what? On the meaning of parameter estimates from reinforcement-learning models
7. Bayes factors for reinforcement-learning models of the Iowa gambling task
8. A tutorial on bridge sampling
9. Bayesian techniques for analyzing group differences in the Iowa gambling task: A case study of intuitive and deliberate decision makers
10. Using Bayesian regression to incorporate covariates into hierarchical cognitive models
11. Summary and future directions
Appendix A: Performance and awareness in the Iowa gambling task
Appendix B: Data from 617 healthy participants performing the Iowa gambling task: A “Many Labs” collaboration
Appendix C: Appendix to Chapter 4: “Validating the PVL-Delta model for the Iowa gambling task”
Appendix D: Appendix to Chapter 5: “Absolute performance of reinforcement-learning models for the Iowa gambling task”
Appendix E: Appendix to Chapter 7: “Bayes factors for reinforcement-learning models of the Iowa gambling task”
Appendix F: Appendix to Chapter 8: “A tutorial on bridge sampling”
Appendix G: Appendix to Chapter 9: “Bayesian techniques for analyzing group differences in the Iowa gambling task: A case study of intuitive and deliberate decision makers”
Appendix H: Appendix to Chapter 10: “Using Bayesian regression to incorporate covariates into hierarchical cognitive models”
References
Nederlandse Samenvatting
Back matter
2020

Manning, C., Norcia, A. M., Scerif, G., Boehm, U. & Wagenmakers, E.-J. (2020). EEG data supporting the published article: Perceptual decision-making in children: Age-related differences and EEG correlates.. Figshare. https://doi.org/10.6084/m9.figshare.12378281

Manning, C., Norcia, A. M., Scerif, G., Boehm, U. & Wagenmakers, E.-J. (2020). Modelling files supporting the published article: Perceptual decision-making in children: Age-related differences and EEG correlates. Figshare. https://doi.org/10.6084/m9.figshare.11931714

2018

de Jonge, P., Morey, R., Roest, A. M., Wardenaar, K. J., Monden, R., Wagenmakers, E.-J. & van Ravenzwaaij, D. (2018). Data for: The comparative evidence basis for the efficacy of second-generation antidepressants in the treatment of depression: A Bayesian Meta-analysis. Mendeley Data. https://doi.org/10.17632/p3k5h38xpn.1

2016

Morey, R. D., Rouder, J. N. & Wagenmakers, E.-J. (2016). Calibrated Bayes Factors Should Not Be Used: A Reply to Hoijtink, van Kooten, and Hulsker. Taylor & Francis. https://doi.org/10.6084/m9.figshare.2252938.v1

van Doorn, J., Wagenmakers, E.-J., Eric-Jan, W., Ly, A. & Marsman, M. (2016). Bayesian Inference for Kendall's Rank Correlation Coefficient. Taylor & Francis. https://doi.org/10.6084/m9.figshare.4452449

2015

Tio, P., Renkewitz, F., Bell, R., Selterman, D., Thomas, S. L., Martinez, T., Voracek, M., Van Doorn, J., Ostkamp, L., Galak, J., Pipitone, R. ., Epskamp, S., Hodsoll, J., Axt, J., Van Rijn, H., Bartmess, E., Strohminger, N., Beyan, L., Hung, C. O.-Y., … Scholz, S. (1-1-2015). Data from: Estimating the reproducibility of psychological science. Singapore Management University. https://doi.org/10.25440/smu.12062757.v1
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- CHDI
  Consultant

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Prof. dr. E.M. (Eric-Jan) Wagenmakers

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