Peer Reviewed Papers and Book Chapters

Waldorp, L., Marsman, M. & Maris, G. (2018). Logistic regression and Ising networks: prediction and estimation when violating lasso assumptions. Behaviormetrika. doi:10.1007/s41237-018-0061-0

Brinkhuis, M.J.S., Savi, A.O., Hofman, A.D., Coomans, F., van der Maas, H.L.J., & Maris, G. (2018). Learning As It Happens: A Decade of Analyzing and Shaping a Large-Scale Online Learning System. Journal of Learning Analytics, 5:2.  doi: 10.18608/jla.2018.52.3

Bergner, Y. & von Davier, A.A. (2018). Process Data in NAEP. Past, Present, and Future. Journal of Educational and Behavioral Statistics, 27. doi:10.3102/1076998618784700

Tijmstra., J. & Bolsinova, M. (2018). On the importance of the speed-ability trade-off when dealing with not reached items. Frontiers in Psychology, 9:964.  doi: 10.3389/fpsyg.2018.00964

Molenaar, D., Bolsinova, M., & Vermunt, J.K. (2018). A semi-parametric within-subject mixture approach to the analyses of responses and response times. British Journal of Mathematical and Statistical Psychology, 71(2), 205-228.

Tijmstra, J., Bolsinova, M., & Jeon, M. (2018). General mixture item response models with different item response structures: Exposition with an application to Likert scales. Behavior research methods, 1-20.

Chow, S.-M., Ou, L., Ciptadi, A., Prince, E., You, D., Hunter, M. D., Rehg, J. M., Rozga, A., & Messinger, D. S. (2018). Differential equation modeling approaches to representing sudden shifts in intensive dyadic interaction data. Psychometrika. doi:

Zhang, F., Zhang, S., Lightsey, C., Harun, S., Wong, P.C. (2017) BGS: A Large-scale Graph Visualization Tool.  IS&T Electronic Imaging: Visualization and Data Analysis, IS&T.

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