Publications

Google Scholar Page

Submitted for Publication

Hoekstra, R. H. A., Huth, K., Sekulovski, N., Delhalle, M., & Sarafoglou, A. (2025). Safeguarding Against Bias Without Preregistration: A Tutorial on Analysis Blinding for Network Analysis.. PsyArXiv

Pfadt, J. M., Bartoš, F., Godmann, H. R., Waaijers, M., Groot, L., Heo, I. , Mensink, L., Nak, J., De Ruiter, J. P., Sarafoglou, A., Siepe, B. S., Arena, G. M., Akrong, E., Aust, F., van den Bergh, D., Brenner, W., Doekemeijer, R. A., Donzallaz, M. C., van Doorn, J., Echevarria, N. O., Finnemann, A., Geller, G., Hato, T., Koskinen, E., Krijgsman, B., Kulbe, L., Lüken, M., Marsman, M., Ott, V. L., Pawel, S., Piestrak, O., de Ron, J., Sekulovski, N., Serry, M., Stefanów, A., Stevenson, N., Sadowski, B., Sopuch, M., Vasileiou, A., Visser, I., Völler, M., Wiechert, S., de Wit, K., Wuth, J., Wagenmakers, E.-J. (2025). A Methodological Metamorphosis: The Rapid Rise of Bayesian Inference and Open Science Practices in Psychology. PsyArXiv.

Sekulovski, N., Arena, G., Haslbeck, J. M. B., Huth, K., Friel, N., & Marsman, M. (2025). A Stochastic Block Prior for Clustering in Graphical Models. PsyArXiv.

Sekulovski, N., Waaijers, M., & Arena, G.(2025). LLM-Based Prior Elicitation for Bayesian Graphical Modeling. PsyArXiv.

In Press

Marsman, M., Waldorp, L. J., .Sekulovski, N., & Haslbeck, J. M. B. (in press). A Bayesian Independent Samples t Test for Parameter Differences in Networks of Binary and Ordinal Variables. Psychometrika.

Sekulovski, N., Blanken, T., Haslbeck, J. M. B., & Marsman, M. (in press). The Impact of Dichotomization on Network Recovery. Behavior Research Methods.

2024

Hoogeveen, S., Borsboom, D., Kucharský, Š, Marsman, M., Molenaar, D., de Ron, J., Sekulovski, N., Visser, I., van Elk, M., & Wagenmakers, E.-J. (2024). Prevalence, Patterns, and Predictors of Paranormal Beliefs in the Netherlands: A Several-Analysts Approach. Royal Society Open Science.

Huth, K., Keetelaar, S., Sekulovski, N., van den Bergh, D., & Marsman, M. (2024). Simplifying Bayesian analysis of graphical models for the social sciences with easybgm: A user-friendly R-package. Advances .in/psychology.

Keetelaar, S., Sekulovski, N., Borsboom, D., & Marsman, M. (2024). Comparing Maximum Likelihood and Pseudo-Maximum Likelihood Estimators for the Ising Model. Advances .in/psychology.

Sekulovski, N., Keetelaar, S., Haslbeck, J. M. B., & Marsman, M. (2024). Sensitivity Analysis of Prior Distributions in Bayesian Graphical Modeling: Guiding Informed Prior Choices for Conditional Independence Testing. Advances .in/psychology.

Sekulovski, N., Keetelaar, S., Huth, K. B. S., Wagenmakers, E.-J., van Bork, R., van den Bergh, D., & Marsman, M. (2024). Testing Conditional Independence in Psychometric Networks: An Analysis of Three Bayesian Methods. Multivariate Behavioral Research.

Sekulovski, N., Marsman, M., & Wagenmakers, E.-J. (2024). A Good Check on the Bayes Factor. Behavior Research Methods.

2023

Sekulovski, N., & Hoijtink, H. (2023). Default Bayes Factor for Testing Null Hypotheses About the Fixed Effects of Linear Two-Level Models. Psychological Methods.