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Results: 94
Number of items: 94
  • Open Access
    Bosma, M. J., Marsman, M., Vermeulen, J., Huth, K. B. S., de Haan, L., Alizadeh, B. Z., Simons, C. J. P., & Schirmbeck, F. (2025). Exploring the Interactions between Psychotic Symptoms, Cognition, and Environmental Risk Factors: A Bayesian Analysis of Networks. Schizophrenia Bulletin, 51(4), 1134–1145. https://doi.org/10.1093/schbul/sbae174
  • Open Access
    Sekulovski, N., Keetelaar, S., Haslbeck, J., & Marsman, M. (2024). Sensitivity analysis of prior distributions in Bayesian graphical modeling: Guiding informed prior choices for conditional independence testing. Advances.in/psychology, 2, Article e92355. https://doi.org/10.56296/aip00016
  • Open Access
    Sekulovski, N., Marsman, M., & Wagenmakers, E.-J. (2024). A Good check on the Bayes factor. Behavior Research Methods, 56(8), 8552–8566. https://doi.org/10.3758/s13428-024-02491-4
  • Open Access
    Briganti, G., Scutari, M., Epskamp, S., Borsboom, D., Hoekstra, R. H. A., Fernandes Golino, H., Christensen, A. P., Morvan, Y., Ebrahimi, O. V., Costantini, G., Heeren, A., de Ron, J., Bringmann, L. F., Huth, K., Haslbeck, J. M. B., Isvoranu, A.-M., Marsman, M., Blanken, T., Gilbert, A., ... McNally, R. J. (2024). Network analysis: An overview for mental health research. International Journal of Methods in Psychiatric Research, 33(4), Article e2034. https://doi.org/10.1002/mpr.2034
  • Open Access
    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, 11(9), Article 240049. https://doi.org/10.1098/rsos.240049
  • Open Access
    Keetelaar, S., Sekulovski, N., Borsboom, D., & Marsman, M. (2024). Comparing maximum likelihood and maximum pseudolikelihood estimators for the Ising model. Advances.in/psychology, 2, Article e25745. https://doi.org/10.56296/aip00013
  • Open Access
    van den Bergh, D. (2024). Embracing uncertainty in multi-step inference. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Sekulovski, N., Keetelaar, S., Huth, K., 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, 59(5), 913-933. https://doi.org/10.1080/00273171.2024.2345915
  • Open Access
    Huth, K. B. S., 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, 2, Article e66366. https://doi.org/10.56296/aip00010
  • Epskamp, S., Fried, E. I., van Borkulo, C. D., Robinaugh, D. J., Marsman, M., Dalege, J., Rhemtulla, M., & Cramer, A. O. J. (2023). Investigating the Utility of Fixed-margin Sampling in Network Psychometrics [Data set]. Taylor & Francis. https://doi.org/10.6084/m9.figshare.23301469.v1
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