I am an assistant professor at the department of psychological methods. I received my PhD in (computational) psychometrics in 2014 at the University of Twente, Enschede. My research has since then focused on formal connections between psychometric and network models and, more recently, the formal psychometric theory for the development of (individual differences in) cognition and psychopathology. At the same time, I also help develop new Bayesian statistical methods for psychological research and JASP. I hold an Innovational Research Incentives Scheme Veni grant awarded by the NWO for the project "The Psychometrics of Learning."
Marsman, M., Borsboom, D., Kruis, J., Epskamp, S., van Bork, S., Waldorp, L.J., van der Maas, H.L.J., & Maris, G.K.J. (in press). An introduction to network psychometrics: Relating Ising network models to item response theory models.
Marsman, M., Waldorp, L.J. & Maris, G.K.J. (in press). A note on large-scale logistic prediction: Using an approximate graphical model to deal with collinearity and missing data. Behaviormetrika.
van der Maas, H.L.J., Kan, K.-J., Marsman, M., & Stevenson, C.E. (2017). Network models for cognitive development and intelligence. Journal of Intelligence, 5(2).
Marsman, M., Maris, G., Bechger, T.M., & Glas, C.A.W. (2017). Turning simulation into estimation: Generalized exchange algorithms for exponential family models. PLoS One, 12(1), e0169787.
Marsman, M., Maris, G.K.J., Bechger, T.M., & Glas, C.A.W. (2016). What can we learn from plausible values? Psychometrika, 81(2), 274-289.
Marsman, M., Maris, G.K.J., Bechger, T.M., & Glas, C.A.W. (2015). Bayesian inference of low-rank Ising networks. Scientific reports, 5(9050).