Publications

For a full overview, see my Google Scholar profile.

First-Author Publications

van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E.-J. (2017). Bayesian inference for Kendall’s rank correlation coefficient. The American Statistician, 71(4), 303–308. DOI

van Doorn, J., Matzke, D., & Wagenmakers, E.-J. (2019). An in-class demonstration of Bayesian inference. Psychology Learning & Teaching, 19(1), 36–45. DOI

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. DOI

van Doorn, J., van den Bergh, D., Böhm, U., Dablander, F., Derks, K., Draws, T., … & Wagenmakers, E.-J. (2021). The JASP guidelines for conducting and reporting a Bayesian analysis. Psychonomic Bulletin & Review, 28, 813–826. DOI

van Doorn, J., Westfall, H. A., & Lee, M. D. (2021). Using the weighted Kendall distance to analyze rank data in psychology. The Quantitative Methods for Psychology, 17(2), 154–165. DOI

van Doorn, J. & Wagenmakers, E.-J. (2021). Strong public claims may not reflect researchers’ private convictions. Significance, 18(1), 44–45. DOI

van Doorn, J., Aust, F., Haaf, J. M., Stefan, A. M., & Wagenmakers, E.-J. (2021). Bayes factors for mixed models. Computational Brain & Behavior, 6, 1–13. DOI

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 & Behavior, 6, 127–139. DOI

van Doorn, J., Haaf, J. M., Stefan, A. M., Wagenmakers, E.-J., Cox, G. E., Davis-Stober, C. P., … & Heck, D. W. (2023). Bayes factors for mixed models: A discussion. Computational Brain & Behavior, 6, 140–158. DOI

Co-Authored Publications

Wagenmakers, E.-J., Love, J., Marsman, M., Jamil, T., Ly, A., Verhagen, J., … van Doorn, J., … & Morey, R. D. (2018). Bayesian inference for psychology. Part II: Example applications with JASP. Psychonomic Bulletin & Review, 25, 58–76. DOI

Jepma, M., Koban, L., van Doorn, J., Jones, M., & Wager, T. D. (2018). Behavioural and neural evidence for self-reinforcing expectancy effects on pain. Nature Human Behaviour, 2, 838–855. DOI

Crüwell, S., van Doorn, J., Etz, A., Makel, M. C., Moshontz, H., Niebaum, J. C., … & Schulte-Mecklenbeck, M. (2019). Seven easy steps to open science. Zeitschrift für Psychologie, 227(4), 237–248. DOI

Crüwell, S., van Doorn, J., Etz, A., Makel, M. C., Moshontz, H., Niebaum, J. C., … & Schulte-Mecklenbeck, M. (2019). 8 easy steps to open science: An annotated reading list. Psychology Archives. DOI

van Dongen, N. N. N., van Doorn, J., Gronau, Q. F., van Ravenzwaaij, D., Hoekstra, R., Haucke, M., … & van de Schoot, R. (2019). Multiple perspectives on inference for two simple statistical scenarios. The American Statistician, 73(sup1), 328–339. DOI

van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E.-J., Derks, K., … & Wagenmakers, E.-J. (2020). A tutorial on conducting and interpreting a Bayesian ANOVA in JASP. L’Année psychologique, 120(1), 73–96. DOI

Ly, A., Stefan, A. M., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., … & 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. DOI

Temp, A. G. M., Ly, A., van Doorn, J., Wagenmakers, E.-J., Tang, Y., Lutz, M. W., … & Heneka, M. T. (2022). A Bayesian perspective on Biogen’s aducanumab trial. Alzheimer’s & Dementia, 18(11), 2283–2284. DOI