Publications

Google Scholar Page

Submitted for publication

Huth, K. B. S., Zavlis, O., Luigjes, J., Galenkamp, H., Lok, A., Bockting, C., Goudriaan, A. E., Marsman, M., & van Holst, R. J. (2024). A Network Perspective on Ethnic, Religious, and Socioeconomic Factors in Alcohol Use—the HELIUS study. PsyArXiv

Sekulovski, N., Blanken, T., Haslbeck, J. M. B., & Marsman, M. (2024). The Impact of Dichotomization on Network Recovery. PsyArXiv.

van den Bergh, D., & Dablander, F. (2022). Flexible Bayesian Multiple Comparison Adjustment Using Dirichlet Process and Beta-Binomial Model Priors. arXiv.

van der Pal, Z., Douw, L., Genis, A., van den Bergh, D., Marsman, M., Schrantee, A., & Blanken, T. (2024). Flexible Bayesian Multiple Comparison Adjustment Using Dirichlet Process and Beta-Binomial Model Priors. arXiv.

Waldorp, L. J., & Marsman, M. (2024). Evolving Networks, Markov Chains and Dynamical Systems.

Zavlis, O., Huth, K. B. S., Luigjes, J., Galenkamp, H., Lok, A., Stronks, K., Bockting, C. L. H., Goudriaan, A., Marsman, M., & van Holst, R. J. (2024). The interplay of alcohol use symptoms and sociodemographic factors in the Netherlands: A network perspective.

Accepted for publication

Bosma, M. J., Vermeulen, J. M., Huth, K. B. S., de Haan, L., Alizadeh, B. Z., Simons, C. J. C., Marsman, M., & Schirmbeck, F. (in press). Exploring the Interactions between Psychotic Symptoms, Cognition, and Environmental Risk Factors: A Bayesian Analysis of Networks. Schizophrenia Bulletin

Marsman, M., van den Bergh, D., & Haslbeck, J. M. B. (in press). Bayesian Analysis of the Ordinal Markov Random Field. Psychometrika. PsyArXiv.

2024

Briganti, G., Scutari, M., Epskamp, S., Borsboom, D., Hoekstra, R. H. A., Golino, H. F., Christensen, A. P., Morvan, Y., Ebrahimi, O. V., Heeren, A., van Bork, R., de Ron, J., Bringmann, L. F., Huth, K. B. S., Haslbeck, J. M. B.,  Isvoranu, A.-M., Marsman, M., Blanken, T. F., Gilbert, A., Henry, T. R., Fried, E. I., & McNally, R. J. (2024). Network analysis: An overview for mental health research. International Journal of Methods in Psychiatric Research, 33(4), e2034.

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), 11240049.

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, e66366.

Keetelaar, S., Sekulovski, N., Borsboom, D., & Marsman, M. (2024). Comparing Maximum Likelihood and Pseudo-Maximum Likelihood Estimators for the Ising Model. Advances .in/psychology, e25745.

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, e92355.

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, 59, 913-933.

Sekulovski, N., Marsman, M., & Wagenmakers, E.-J. (2024). A Good Check on the Bayes Factor. Behavior Research Methods, 56, 8552–8566.

2023

Huth, K. B. S., de Ron, J., Goudriaan, A. E., Luigjes, J., Mohammadi, R., van Holst, R. J., Wagenmakers, E.-J., & Marsman, M. (2023). Bayesian analysis of cross-sectional networks: A tutorial in R and JASP. Advances in Methods and Practices in Psychological Science, 6, 1-18.

Marsman, M., & Huth, K. B. S. (2023). Idiographic Ising and Divide and Color Models: Encompassing networks for heterogeneous binary data. Multivariate Behavioral Research, 58, 787-814.

Marsman, M., Waldorp, L. J., & Borsboom, D. (2023). Towards an encompassing theory of network models: Reply to Brusco, Steinley, Hoffman, Davis-Stober, & Wasserman. Psychological Methods, 28, 757-764.

2022

Huth, K. B. S., Waldorp, L. J., Luigjes, J., Goudriaan, A. E., van Holst, R. J., & Marsman, M. (2022). A note on the Structural Change Test in finite samples: Using a permutation approach to estimate the sampling distribution. Psychometrika, 87, 1064-2080.

Marsman, M., & Rhemtulla, M. (2022). Guest Editors’ Introduction to The Special Issue “Network Psychometrics in Action”: Methodological Innovations Inspired by Empirical Problems. Psychometrika, 87, 1–11.

Marsman, M., Huth, K., Waldorp, L. J., & Ntzoufras, I. (2022). Objective Bayesian Edge Screening and Structure Selection for Networks of Binary Variables. Psychometrika, 87, 47–82.

Waldorp, L. J., & Marsman, M. (2022). Relations between networks, regression, partial correlation, and latent variable models. Multivariate Behavioral Research, 57, 994-1006.

2021

Haslbeck, J., Epskamp, S., Marsman, M., & Waldorp, L. J. (2021). Interpreting the Ising model: The input matters. Multivariate Behavioral Research, 56, 303-313.

Huth, K. B. S., Luigjes, J., Marsman, M., Goudriaan, A. E., & van Holst, R. J. (2021). Modeling alcohol use disorder as a set of interconnected symptoms -Assessing differences between clinical and populationsamples and across external factors. Addictive Behaviors, 125, 107128.

2019

Marsman, M., Sigurdardottir, H., Bolsinova, M., & Maris, G. K. J. (2019). Characterizing the manifest probability distributions of three latent trait models for accuracy and response time. Psychometrika, 84, 870-891.

Marsman, M., Tanis, C., Bechger, T. M., & Waldorp, L. J. (2019). Network psychometrics in educational practice. Maximum likelihood estimation of the Curie-Weiss model. In Theoretical and Practical Advances in Computer-Based Educational Measurement (pp. 93–120). Springer Nature.

Waldorp, L. J., Marsman, M., & Maris, G. K. J. (2019). Logistic regression and Ising networks: Prediction and estimation when violating lasso assumptions. Behaviormetrika, 46, 49-72.

2018

Marsman, M., Borsboom, D., Kruis, J., Epskamp, S., van Bork, R., Waldorp, L. J., Maas, H. L. J. van der, & Maris, G. (2018). An introduction to network psychometrics: Relating Ising network models to item response theory models. Multivariate Behavioral Research, 53, 15–35.

2017

Epskamp, S., Kruis, J., & Marsman, M. (2017). Estimating psychopathological networks: Be careful what you wish for. PloS One, 12, e0179891.

Marsman, M., Waldorp, L. J. & Maris, G. K. J. (2017). A note on large-scale logistic prediction: Using an approximate graphical model to deal with collinearity and missing data. Behaviormetrika, 44, 513-534.

2015

Marsman, M., Maris, G., Bechger, T., & Glas, C. (2015). Bayesian inference for low-rank Ising networks. Scientific Reports, 5, 9050.