Johnny van Doorn

Johnny van Doorn

Assistant Professor, Psychological Methods

Posts by Collection

portfolio

publications

Bayesian inference for psychology. Part II: Example applications with JASP

Published in Psychonomic Bulletin & Review, 2018

Demonstrates practical applications of Bayesian hypothesis testing using JASP for common psychological research designs.

Recommended citation: 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., et al. (2018). "Bayesian inference for psychology. Part II: Example applications with JASP." Psychonomic Bulletin & Review, 25, 58-76. https://doi.org/10.3758/s13423-017-1323-7

Behavioural and neural evidence for self-reinforcing expectancy effects on pain

Published in Nature Human Behaviour, 2018

Examines two mechanisms underlying self-reinforcing expectancy effects in the pain domain: modulation of perception and biased learning.

Recommended citation: 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. https://doi.org/10.1038/s41562-018-0455-8

Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance

Published in Journal of Clinical Epidemiology, 2018

Outlines a network method to synthesize a literature overview from search results obtained by multiple team members, illustrated with the dispersed ANCOVA literature.

Recommended citation: Derks, K., Burger, J., van Doorn, J.,";";"; & Wagenmakers, E.-J. (2018). "Network Models to Organize a Dispersed Literature: The Case of Misunderstanding Analysis of Covariance." Journal of Clinical Epidemiology. https://doi.org/10.1016/j.jclinepi.2018.10.024

Seven Easy Steps to Open Science

Published in Zeitschrift für Psychologie, 2019

An accessible introduction to open science practices in the form of an annotated reading list of seven peer-reviewed articles.

Recommended citation: Crüwell, S., van Doorn, J., Etz, A.,"; et al. (2019). "Seven Easy Steps to Open Science." Zeitschrift für Psychologie, 227(4), 237-248. https://doi.org/10.1027/2151-2604/a000387

Bayesian estimation of Kendall’s τ using a latent normal approach

Published in Statistics & Probability Letters, 2019

Demonstrates how introducing a latent normal level to ordinal data yields Bayesian inference for Kendall’s rank correlation coefficient.

Recommended citation: van Doorn, J., Ly, A., Marsman, M., & Wagenmakers, E.-J. (2019). "Bayesian estimation of Kendall's τ using a latent normal approach." Statistics & Probability Letters, 145, 268-272. https://doi.org/10.1016/j.spl.2018.10.004

Multiple Perspectives on Inference for Two Simple Statistical Scenarios

Published in The American Statistician, 2019

Empirical comparison of how different statistical frameworks (frequentist vs. Bayesian, estimation vs. testing) impact qualitative conclusions for real data.

Recommended citation: van Dongen, N. N. N., van Doorn, J. B., Gronau, Q. F., van Ravenzwaaij, D., Hoekstra, R., Haucke, M. N.,"; et al. (2019). "Multiple Perspectives on Inference for Two Simple Statistical Scenarios." The American Statistician, 73(sup1), 328-339. https://doi.org/10.1080/00031305.2019.1565553

An In-Class Demonstration of Bayesian Inference

Published in Psychology Learning & Teaching, 2019

Revisits Fisher’s “The Lady Tasting Tea” from a Bayesian perspective, demonstrating how a classroom tasting experiment can familiarize students with key concepts of Bayesian inference.

Recommended citation: van Doorn, J., Matzke, D., & Wagenmakers, E.-J. (2019). "An In-Class Demonstration of Bayesian Inference." Psychology Learning & Teaching, 19(1), 36-45. https://doi.org/10.1177/1475725719848574

Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman’s ρ

Published in Journal of Applied Statistics, 2020

Develops Bayesian hypothesis tests for rank-based problems using a latent normal representation consistent with the ordinal information in the data.

Recommended citation: 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

A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP

Published in L'Année psychologique, 2020

A step-by-step tutorial for conducting and interpreting Bayesian ANOVA analyses using the JASP software package.

Recommended citation: van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E.-J., Chober, C., Ly, A., & Wagenmakers, E.-J. (2020). "A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP." L'Année psychologique, 120(1), 73-96. https://doi.org/10.3917/anpsy1.201.0073

The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test

Published in Computational Brain & Behavior, 2020

Argues that Jeffreys’ Bayesian methodology provides a workable alternative to the p value, being relevant, objective, calibrated, and easy to apply with JASP.

Recommended citation: Ly, A., Stefan, A. M., van Doorn, J., Dablander, F., van den Bergh, D., Sarafoglou, A., Kucharský, Š., Derks, K., Gronau, Q. F., Raj, A., Böhm, U., van Kesteren, E.-J.,"; et al. (2020). "The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the P Value Hypothesis Test." Computational Brain & Behavior, 3, 153-161. https://doi.org/10.1007/s42113-019-00070-x

talks

teaching

Bayesian Statistics

Undergraduate course, UvA, FMG, 2023

Undergraduate course in the Psychological Methods specialization of the Psychology Bachelor’s program.