Google Scholar Page

Submitted for publication

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

Sekulovski, N*., Keetelaar, S., Haslbeck, J. M. B., & Marsman, M. (2023). Sensitivity Analysis of Prior Distributions in Bayesian Graphical Modeling: Guiding Informed Prior Choices for Conditional Independence Testing. PsyArXiv.

In press

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

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


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

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.


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