Publications

On this page you will find some of our most influential papers within certain categories. If you want to explore more of our papers, please visit our database.


Questionable and responsible practices in quantitative, qualitative and mixed methods research

Wicherts, J. M., Veldkamp, C. L., Augusteijn, H. E., Bakker, M., Van Aert, R. C., & Van Assen, M. A. (2016). Degrees of freedom in planning, running, analyzing, and reporting psychological studies: A checklist to avoid p-hacking. Frontiers in psychology, 7, 1832.

Preregistration of qualitative research

Haven, T., & Van Grootel, D. L. (2019). Preregistering qualitative research. Accountability in research, 26(3), 229–244.

Open science practices; data sharing and open access


Haven, T. L., Abunijela, S., & Hildebrand, N. (2023). Biomedical supervisors' role modeling of open science practices. eLife, 12, e83484.

Van Lissa, C. J., Brandmaier, A. M., Brinkman, L., Lamprecht, A.-L., Peikert, A., Struiksma, M. E., & Vreede, B. M. I. (2021). WORCS: A workflow for open reproducible code in science. Data Science, 4(1), 29–49. https://doi.org/10.3233/DS-210031


Reproducibility, replicability, and robustness of published findings

Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2016). The prevalence of statistical reporting errors in psychology (1985-2013). Behavior Research Methods, 48 (4), 1205-1226.

Maassen, E., Van Assen, M. A., Nuijten, M. B., Olsson-Collentine, A., & Wicherts, J. M. (2020). Reproducibility of individual effect sizes in meta-analyses in psychology. PloS one, 15(5), e0233107.

van Aert, R. C. M., Nuijten, M. B., Olsson-Collentine, A., Stoevenbelt, A. H., van den Akker, O. R., Klein, R. A., & Wicherts, J. M. (2023). Comparing the prevalence of statistical reporting inconsistencies in COVID-19 preprints and matched controls: A registered report. Royal Society Open Science, 10(8), 1–16.

The effectiveness of preregistration in psychology

van den Akker, O. R., van Assen, M. A., Bakker, M., Elsherif, M., Wong, T. K., & Wicherts, J. M. (2024). Preregistration in practice: A comparison of preregistered and non-preregistered studies in psychology. Behavior Research Methods, 56(6), 5424-5433.

van den Akker, O., Weston, S., Campbell, L., Chopik, B., Damian, R., Davis-Kean, P., ... & Bakker, M. (2021). Preregistration of secondary data analysis: A template and tutorial. Meta-psychology, 5, 2625.

van den Akker, O. R., van Assen, M. A., Enting, M., de Jonge, M., Ong, H. H., Rüffer, F., ... & Bakker, M. (2023). Selective hypothesis reporting in psychology: Comparing preregistrations and corresponding publications. Advances in Methods and Practices in Psychological Science, 6(3), 25152459231187988.

Bakker, M., Veldkamp, C. L., van Assen, M. A., Crompvoets, E. A., Ong, H. H., Nosek, B. A., ... & Wicherts, J. M. (2020). Ensuring the quality and specificity of preregistrations. PLoS biology, 18(12), e3000937.

Van Lissa, C. J. (2023). Complementing preregistered confirmatory analyses with rigorous, reproducible exploration using machine learning. Religion, Brain & Behavior, 13(3), 347-351.

Statistical power and interpreting statistical results

van den Akker, O. R., Wicherts, J. M., Alvarez, L. D., Bakker, M., & van Assen, M. A. (2023). How do psychology researchers interpret the results of multiple replication studies?. Psychonomic Bulletin & Review, 30(4), 1609-1620.

Tendeiro, J. N., Kiers, H. a. L., Hoekstra, R., Wong, T. K., & Morey, R. D. (2024). Diagnosing the misuse of the Bayes factor in applied research. Advances in Methods and Practices in Psychological Science, 7(1).

















Meta-analysis & heterogeneity

Olsson-Collentine, A., Wicherts, J. M., & van Assen, M. A. (2020). Heterogeneity in direct replications in psychology and its association with effect size. Psychological Bulletin, 146(10), 922.

Van Lissa, C. J., van Erp, S., & Clapper, E. B. (2023). Selecting relevant moderators with Bayesian regularized meta‐regression. Research Synthesis Methods, 14(2), 301-322.  

Van Assen, Marcel ALM, Robbie van Aert, and Jelte M. Wicherts. Meta-analysis using effect size distributions of only statistically significant studies. Psychological methods 20.3 (2015): 293.

Van Aert, R. C., Wicherts, J. M., & Van Assen, M. A. (2019). Publication bias examined in meta-analyses from psychology and medicine: A meta-meta-analysis. PloS one, 14(4), e0215052.

Augusteijn, H. E., van Aert, R., & van Assen, M. A. (2019). The effect of publication bias on the Q test and assessment of heterogeneity. Psychological methods, 24(1), 116.

Van Assen, M. A., Van Den Akker, O. R., Augusteijn, H. E., Bakker, M., Nuijten, M. B., Olsson-Collentine, A., ... & Van Aert, R. C. (2023). The Meta-Plot. Zeitschrift für Psychologie.

van Aert, R. C. M., & Wicherts, J. M. (2024). Correcting for outcome reporting bias in a meta-analysis: A meta-regression approach. Behavior Research Methods, 56(3), 1994–2012.

van Aert, R.C.M. (in press). Meta-analyzing non-preregistered and preregistered studies. Psychological Methods.

van Aert, R. C. M. (2023). Meta‐analyzing partial correlation coefficients using Fisher’s z transformation. Research Synthesis Methods, 14(5), 768–773.

van Aert, R. C. M., & Goos, C. (2023). A critical reflection on computing the sampling variance of the partial correlation coefficient. Research Synthesis Methods, 14(3), 520–525.

Publication bias

Olsson-Collentine, A., Van Assen, M. A., & Hartgerink, C. H. (2019). The prevalence of marginally significant results in psychology over time. Psychological science, 30(4), 576-586.

Van Aert, R. C., Wicherts, J. M., & van Assen, M. A. (2016). Conducting meta-analyses based on p values: Reservations and recommendations for applying p-uniform and p-curve. Perspectives on Psychological Science, 11(5), 713-729.

Van Assen, M. A., Van Aert, R. C., Nuijten, M. B., & Wicherts, J. M. (2014). Why publishing everything is more effective than selective publishing of statistically significant results. PLoS one, 9(1), e84896.

Theory development using machine learning

Van Lissa, C. J. (2023). Developmental data science: How machine learning can advance theory formation in developmental psychology. Infant and Child Development, 32(6), e2370.