Dr. J.M. (Julia) Haaf
Faculty of Social and Behavioural Sciences
Programme group Psychological Methods
Visiting address
- Nieuwe Achtergracht 129
Postal address
- Postbus 15906
1001 NK Amsterdam
Contact details
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Publications
- refereed (30)
- academic (3)
- recognitions (9)
- supervised theses (1)
- working papers / preprints (1)
- datasets (1)
2023
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]
2022
- Bartoš, F., Aust, F., & Haaf, J. M. (2022). Informed Bayesian survival analysis. BMC Medical Research Methodology, 22, [238]. https://doi.org/10.1186/s12874-022-01676-9 [details]
- Donzallaz, M. C., Haaf, J. M., & Stevenson, C. E. (2022). Creative or Not? Hierarchical Diffusion Modeling of the Creative Evaluation Process. Journal of Experimental Psychology: Learning Memory and Cognition. https://doi.org/10.1037/xlm0001177
- Hoogeveen, S., Haaf, J. M., Bulbulia, J. A., Ross, R. M., McKay, R., Altay, S., Bendixen, T., Berniūnas, R., Cheshin, A., Gentili, C., Georgescu, R., Gervais, W. M., Hagel, K., Kavanagh, C., Levy, N., Neely, A., Qiu, L., Rabelo, A., Ramsay, J. E., ... van Elk, M. (2022). The Einstein effect provides global evidence for scientific source credibility effects and the influence of religiosity. Nature Human Behaviour, 6(4), 523-535. https://doi.org/10.1038/s41562-021-01273-8 [details]
- Rouder, J. N., Schnuerch, M., Haaf, J. M., & Morey, R. D. (2022). Principles of Model Specification in ANOVA Designs. Computational Brain and Behavior. https://doi.org/10.1007/s42113-022-00132-7
- Schnuerch, M., Haaf, J. M., Sarafoglou, A., & Rouder, J. N. (2022). Meaningful Comparisons With Ordinal-Scale Items. Collabra: Psychology, 8, [38594]. https://doi.org/10.1525/collabra.38594 [details]
- Van Geert, E., Moors, P., Haaf, J., & Wagemans, J. (2022). Same stimulus, same temporal context, different percept? Individual differences in hysteresis and adaptation when perceiving multistable dot lattices. I-Perception, 13(4). https://doi.org/10.1177/20416695221109300 [details]
2021
- 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). https://doi.org/10.1177/25152459211031256 [details]
- Haaf, J. M., & Rouder, J. N. (2021). Does Every Study? Implementing Ordinal Constraint in Meta-Analysis. Psychological Methods. https://doi.org/10.31234/osf.io/hf9se, https://doi.org/10.1037/met0000428
- Haaf, J. M., Rhodes, S., Naveh-Benjamin, M., Sun, T., Snyder, H. K., & Rouder, J. N. (2021). Revisiting the remember-know task: Replications of Gardiner and Java (1990). Memory & Cognition, 49(1), 46-66. https://doi.org/10.3758/s13421-020-01073-x [details]
- Rouder, J. N., & Haaf, J. M. (2021). Are there reliable qualitative individual difference in cognition? Journal of Cognition, 4(1), [46]. https://doi.org/10.5334/JOC.131 [details]
- Sarafoglou, A., Haaf, J. M., Ly, A., Gronau, Q. F., Wagenmakers, E. J., & Marsman, M. (2021). Evaluating Multinomial Order Restrictions With Bridge Sampling. Psychological Methods, Advance online publication. https://doi.org/10.1037/met0000411
- Tierney, W., Hardy, J., Ebersole, C. R., Viganola, D., Clemente, E. G., Gordon, M., Hoogeveen, S., Haaf, J., Dreber, A., Johannesson, M., Pfeiffer, T., Huang, J. L., Vaughn, L. A., DeMarree, K., Igou, E. R., Chapman, H., Gantman, A., Vanaman, M., Wylie, J., ... Uhlmann, E. L. (2021). A creative destruction approach to replication: Implicit work and sex morality across cultures. Journal of Experimental Social Psychology, 93, [104060]. https://doi.org/10.1016/j.jesp.2020.104060 [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. https://doi.org/10.3758/s13423-020-01798-5 [details]
- 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]
2020
- Haaf, J. M., Merkle, E. C., & Rouder, J. N. (2020). Do items order? The psychology in IRT models. Journal of Mathematical Psychology, 98, [102398]. https://doi.org/10.1016/j.jmp.2020.102398 [details]
2019
- Aust, F., Haaf, J. M., & Stahl, C. (2019). A Memory-Based Judgment Account of Expectancy-Liking Dissociations in Evaluative Conditioning. Journal of Experimental Psychology Learning Memory and Cognition, 45(3), 417-439. https://doi.org/10.1037/xlm0000600 [details]
- Haaf, J. M., & Rouder, J. N. (2019). Some do and some don't? Accounting for variability of individual difference structures. Psychonomic Bulletin & Review, 26(3), 772-789. https://doi.org/10.3758/s13423-018-1522-x [details]
- Rouder, J. N., & Haaf, J. M. (2019). A psychometrics of individual differences in experimental tasks. Psychonomic Bulletin & Review, 26(2), 452-467. https://doi.org/10.3758/s13423-018-1558-y [details]
- Rouder, J. N., Haaf, J. M., & Snyder, H. K. (2019). Minimizing Mistakes In Psychological Science. Advances in Methods and Practices in Psychological Science, 2(1), 3-11. https://doi.org/10.1177/2515245918801915 [details]
- Rouder, J. N., Haaf, J. M., Davis-Stober, C. P., & Hilgard, J. (2019). Beyond Overall Effects: A Bayesian Approach to Finding Constraints in Meta-Analysis. Psychological Methods, 24(5), 606-621. https://doi.org/10.1037/met0000216 [details]
- Snyder, H. K., Rafferty, S. M., Haaf, J. M., & Rouder, J. N. (2019). Common or distinct attention mechanisms for contrast and assimilation? Attention, Perception & Psychophysics, 81(6), 1944-1950. https://doi.org/10.3758/s13414-019-01713-8 [details]
2018
- Etz, A., Haaf, J. M., Rouder, J. N., & Vandekerckhove, J. (2018). Bayesian Inference and Testing Any Hypothesis You Can Specify. Advances in Methods and Practices in Psychological Science, 1(2), 281-295. https://doi.org/10.1177/2515245918773087 [details]
- Heycke, T., Gehrmann, S., Haaf, J. M., & Stahl, C. (2018). Of two minds or one? A registered replication of Rydell et al. (2006). Cognition & Emotion, 32(8), 1708-1727. https://doi.org/10.1080/02699931.2018.1429389
- Rouder, J. N., & Haaf, J. M. (2018). Power, Dominance, and Constraint: A Note on the Appeal of Different Design Traditions. Advances in Methods and Practices in Psychological Science, 1(1), 19-26. https://doi.org/10.1177/2515245917745058 [details]
- Rouder, J. N., Haaf, J. M., & Aust, F. (2018). From theories to models to predictions: A Bayesian model comparison approach. Communication Monographs, 85(1), 41-56. https://doi.org/10.1080/03637751.2017.1394581
- Rouder, J. N., Haaf, J. M., & Vandekerckhove, J. (2018). Bayesian inference for psychology, part IV: parameter estimation and Bayes factors. Psychonomic Bulletin & Review, 25(1), 102-113. https://doi.org/10.3758/s13423-017-1420-7
2017
- Haaf, J. M., & Rouder, J. N. (2017). Developing Constraint in Bayesian Mixed Models. Psychological Methods, 22(4), 779-798. https://doi.org/10.1037/met0000156
- Thiele, J. E., Haaf, J. M., & Rouder, J. N. (2017). Is there variation across individuals in processing? Bayesian analysis for systems factorial technology. Journal of Mathematical Psychology, 81, 40-54. https://doi.org/10.1016/j.jmp.2017.09.002
2016
- Stahl, C., Haaf, J., & Corneille, O. (2016). Subliminal Evaluative Conditioning? Above-Chance CS Identification May Be Necessary and Insufficient for Attitude Learning. Journal of Experimental Psychology. General, 145(9), 1107-1131. https://doi.org/10.1037/xge0000191
2023
- 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]
- 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]
2019
- 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]
Prize / grant
- Haaf, J. (2020). Anne Anastasi Dissertation Award.
Journal editor
- Haaf, J. (editor) (2020-2022). Collabra: Psychology (Journal).
- Haaf, J. (editor) (2020-2022). Behavior Research Methods (Journal).
Talk / presentation
- Haaf, J. (invited speaker) (14-11-2019). Bayesian hierarchical modeling of cognitive processes: Benefits and pitfalls, Current Trends in Mathematical Psychology, Montreal.
- Haaf, J. (invited speaker) (23-9-2019). Does Everyone? Modeling Individual Differences in Cognitive Tasks, University of Tuebingen.
- Haaf, J. (keynote speaker) (13-9-2019). Modeling Individual Differences in a Bayesian Framework, Universität Potsdam.
- Haaf, J. (invited speaker) (29-4-2019). A Bayesian modeling approach for individual differences, Laboratory for Experimental Psychology, Department of Brain and Cognition, KU Leuven, Leuven, Belgium..
- Haaf, J. (speaker) (18-2-2019). The Crisis of Replicability in Psychology: A Statistical Perspective, University of Padova.
Others
- Haaf, J. (organiser) & Hilgard, J. (organiser) (8-2-2019). Symposium at the SPSP Annual Convention, Portland (organising a conference, workshop, ...).
2020
- 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. PsyArXiv. https://doi.org/10.31234/osf.io/cb9er
2022
- Bartoš, F., Aust, F. & Haaf, J. M. (2022). Informed Bayesian survival analysis. Figshare. https://doi.org/10.6084/m9.figshare.c.6191444.v1
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Ancillary activities
No ancillary activities
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.