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.

da Silva, M. A., de Oliveira, E. S., von Davier, A. A., & Bazán, J. L. (2017). Estimating the DINA model parameters using the No‐U‐Turn Sampler. Biometrical Journal.

Chopade, P., Zhan, J., (2017) A Framework for Community Detection in Large Networks using a Game-theoretic Modeling. IEEE Transactions on Big Data, 3(3), (pp. 276-288). DOI: 10.1109/TBDATA.2016.2628725.

Chopade, P., Yudelson, M., Deonovic, B., & von Davier, A. A. (2018). Modeling Dynamic Team Interactions for Intelligent Tutoring. In (ed.) Building Intelligent Tutoring Systems for Teams (Research on Managing Groups and Teams) v. 19, p.131 - 151. Emerald Publishing Limited

Agard, C., von Davier, A.A. (2017). The Virtual World and Reality of Testing: Building Virtual Assessments. In Hong, J., Lissitz, R.W. (Eds), Technology Enhanced Innovative Assessment: Development, Modeling, and Scoring from an Interdisciplinary Perspective (pp. 1-30). Charlotte, NC: Information Age Publishing.

Stay up to date with announcements from ACTNext x