I am a postdoc with Dora Matzke, Mark Hinder (University of Tasmania), and Andrew Heathcote (University of Newcastle) and a teacher at the Psychological Methods Unit of the University of Amsterdam. I did my PhD with Eric-Jan Wagenmakers on both the theoretical development and the practical implementation of Bayesian analyses, with a particular focus on Bayesian model comparison and computational methods for estimating Bayes factors. My postdoc is concerned with response-inhibition models for how we cancel and modify movements and cognitive models for improving the diagnosticity of eyewitness memory choices.
Publications by Quentin Gronau
Gronau, Q.F., Hinder, M.R., Salomoni, S.E., Matzke, D., & Heathcote, A. (2023). A unified account of simple and response-selective inhibition. Manuscript submitted for publication.
van Doorn, J., Haaf, J.M., Stefan, A.M., Wagenmakers, E.-J., Cox, G.E., Davis-Stober, C.P., Heathcote, A., Heck, D., Kalish, M., Kellen, D., Matzke, D., Morey, R.D., Nicenboim, B., van Ravenzwaaij, D., Rouder, J.N., Shiffrin, R.M., Schad, D.J., Singmann, H., Vasishth, S., Verissimo, J., Chandramouli, S., Dunn, J.C., Gronau, Q.F., Navarro, D., Yadav, H., Bockting, F., Linde, M., McMullin, S.D., Schnuerch, M., & Aust. F. (2023). Bayes factors for mixed models: A discussion. Computational Brain & Behavior, 6, 140–158.
Haaf, J. M., Hoogeveen, S., Berkhout, S., Gronau, Q. F., & Wagenmakers, E. J. (2020). A Bayesian Multiverse Analysis of Many Labs 4: Quantifying the Evidence against Mortality Salience. PsyArXiv. [GitHub]
Sarafoglou, A., Haaf, J. M., Ly, A., Gronau, Q. F., Wagenmakers, E., & Marsman, M. (in press). Evaluating Multinomial Order Restrictions with Bridge Sampling. Psychological Methods.
van Doorn, J., van den Bergh, D., Dablander, F., van Dongen, N., Derks, K., Evans, N., Gronau, Q., Haaf, J. M., Kunisato, Y., Ly, A., Marsman, M., Sarafoglou, A., Stefan, A., & Wagenmakers, E. (2021). Strong Public Claims May Not Reflect Researchers’ Private Convictions. Significance, 18, 44-45.
Boehm, U., Evans, N.J., Gronau, Q.F, Matzke, D., Wagenmakers, E.-J., Heathcote, A. (2023). Inclusion Bayes Factors for mixed hierarchical Diffusion Decision Models. Psychological Methods.
Wagenmakers, E.-J., Gronau, Q. F., & Vandekerckhove, J. (submitted). Five Bayesian intuitions for the
stopping rule principle. Manuscript submitted for publication.Gronau, Q. F., Heck, D. W., Berkhout, S. W., Haaf, J. M., & Wagenmakers, E.-J. (in press). A primer on
Bayesian model-averaged meta-analysis. Advances in Methods and Practices in Psychological Science, 4(3), 25152459211031256.Stefan, A., Katsimpokis, D., Gronau, Q. F., & Wagenmakers, E.-J. (submitted). Expert agreement in prior
elicitation and its effects on Bayesian inference. Manuscript submitted for publication.Gronau, Q. F., Raj, K. N. A., & Wagenmakers, E.-J. (in press). Informed Bayesian inference for the A/B test. Journal of Statistical Software.
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), e0245048.
Bergh, D. van den, Clyde, M. A., Komarlu Narendra 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.
van Doorn, J., van den Bergh, D., Boehm, U., Dablander, F., Derks, K., Draws, T., Evans, N.J., Gronau, Q. F., Haaf, J. M., Hinne, M., Kucharsky, S., Ly, A., Marsman, M., Matzke, D., Raj, A.K.N., Sarafoglou, A., Stefan, A., Voelkel, A.G., & Wagenmakers, E.-J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28, 813–826.
Wagenmakers, E.-J., Gronau, Q. F., Dablander, F., & Etz, A. (2020). The support interval. Erkenntnis.
Gronau, Q. F., & Lee, M. D. (2020). Bayesian inference for multidimensional scaling representations with psychologically interpretable metrics. Computational Brain & Behavior, 3(3), 322–340.
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.
Landy, J. F., Jia, M. (Liam), 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.
Gronau, Q. F., Ly, A., & Wagenmakers, E.-J. (2020). Informed Bayesian t-tests. The American Statistician, 74(2), 137–143.
Gronau, Q. F., Singmann, H., & Wagenmakers, E.-J. (2020). bridgesampling: An R package for estimating normalizing constants. Journal of Statistical Software, 92(1), 1–29.
van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E.-J., Derks, K., Dablander, F., Gronau, Q. F., …, Matzke, D., & Wagenmakers, E.-J. (2020). A tutorial on conducting and interpreting a Bayesian ANOVA in JASP. L’ Année Psychologique, 120, 73-96.
Ly, A., Stefan, A., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., Kucharsky, S., Derks,
K., Gronau, Q. F., …, Matzke, D., …, 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, 153-161.Gronau, Q.F., Heathcote, A., & Matzke, D. (2020). Computing Bayes factors for evidence-accumulation models using Warp-III bridge sampling. Behavioral Research Methods, 52, 918-937. [Supplementary Materials]
Gronau, Q. F., Raj K. N., A., & Wagenmakers, E.-J. (2019). abtest: Bayesian A/B testing. R package
version 0.2.0.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.
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.
Dongen, N. N. N. van, Doorn, J. B. van, Gronau, Q. F., Ravenzwaaij, D. van, 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. The American Statistician, 73(sup1), 328–339.
Boffo, M., Zerhouni, O., Gronau, Q. F., van Beek, R. J. J., Nikolaou, K., Marsman, M., & Wiers, R. W. (2019). Cognitive bias modification for behavior change in alcohol and smoking addiction: Bayesian meta-analysis of individual participant data. Neuropsychology Review, 29(1), 52–78.
Gronau, Q. F., & Wagenmakers, E.-J. (2019). Rejoinder: More limitations of Bayesian leave-one-out cross-validation. Computational Brain & Behavior, 2(1), 35–47.
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.
Love, J., Selker, R., Marsman, M., Jamil, T., Dropmann, D., Verhagen, J., Ly, A., Gronau, Q. F., …, Matzke, D., …, & Wagenmakers, E.-J. (2019). JASP- Graphical statistical software for common statistical designs. Journal of Statistical Software, 88, 1-17.
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, 261-284.
Gronau, Q. F. & Singmann, H. (2018). bridgesampling: Bridge sampling for marginal likelihoods
and Bayes Factors. R package version 0.7-2.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.
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.
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.
Etz, A., Gronau, Q. F., Dablander, F., Edelsbrunner, P. A., & Baribault, B. (2018). How to become a Bayesian in eight easy steps: An annotated reading list. Psychonomic Bulletin & Review, 25(1), 219–234.
Wagenmakers, E.-J., Marsman, M., Jamil, T., Ly, A., Verhagen, A.J., Love, J., …, Matzke, D., et al. (2018). Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications. Psychonomic Bulletin & Review, 25, 35-57.
Wagenmakers, E.-J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, A.J., …,Gronau, Q.F., …, Matzke, D., et al. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25, 58-76.
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.
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.
Gronau, Q. F., Erp, S. V., 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.
Gronau, Q. F., Sarafoglou, A., Matzke, D., Ly, A., Boehm, U., Marsman, M., et al. (2017). A tutorial on bridge sampling. Journal of Mathematical Psychology, 81, 80-97.
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.
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(1), 160082.
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.
Wagenmakers, E.-J., Beek, T.F., Rotteveel, M., Gierholz, A., Matzke, D., Steingrover, H., Ly, A., Verhagen,
A. J., Selker, R., Sasiadek, A., Gronau, Q.E., Love, J., & Pinto, Y. (2015). Turning the hands of time again: A purely confirmatory replication study and a Bayesian analysis. Frontiers in Psychology: Cognition, 6:494.van Elk, M., Matzke, D., Gronau, Q, 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: Personality and Social Psychology, 6:1365.
Gronau, Q. F. & Oreel, T. (2014). Including prior information in Bayesian procedures. In H. J., Adér, G. J.
& Mellenbergh (Eds.), Advising on research methods: Selected topics (pp. 67-85). Johannes van
Kessel Publishing: Huizen.