Research Interests
My primary research pertains to the use of latent variable modeling, machine learning, and other quantitative methods to solve practical problems in educational and psychological testing. Here are a few of my current research interests:
-
Latent variable modeling: missing data, response times, diagnostic classification, Bayesian estimation;
-
Longitudinal models for learning and interventions;
-
Analysis of complex data (e.g., log data) in computer-based testing and learning environments.
Education
Quantitative Psychology, Ph.D., University of Illinois Urbana-Champaign
Applied Mathematics, MS, University of Illinois Urbana-Champaign
Psychology, BA, Bryn Mawr College
Mathematics, BA, Haverford College
Courses Taught
- STAT 428 - Spring 2021
- PSYC 490 - Fall 2020
- Online workshop on Statistical Learning of Process Data (Video recording)
Additional Campus Affiliations
Assistant Professor, Statistics
External Links
Highlighted Publications
Fang, G., Xu, X., Guo, J., Ying, Z., & Zhang, S. (2020). Identifiability of Bifactor Models. Statistica Sinica. http://www3.stat.sinica.edu.tw/ss_newpaper/SS-2020-0386_na.pdf
Wang, S., Zhang, S., & Shen, Y. (2020). A joint modeling framework of responses and response times to assess learning outcomes. Multivariate Behavioral Research, 55(1), 49-68. https://doi.org/10.1080/00273171.2019.1607238
Recent Publications
Chang, H. H., Wang, C., & Zhang, S. (2021). Statistical Applications in Educational Measurement. Annual Review of Statistics and Its Application, 8, 439-461. https://doi.org/10.1146/annurev-statistics-042720-104044
Fu, Z., Zhang, S., Su, Y., Shi, N., & Tao, J. (2021). A Gibbs sampler for the multidimensional four‐parameter logistic item response model via a data augmentation scheme. British Journal of Mathematical and Statistical Psychology. https://doi.org/10.1111/bmsp.12234
Zhang, S., Bergner, Y., Ditrapani, J., & Jeon, M. (2021). Modeling the interaction between resilience and ability in assessments with allowances for multiple attempts. Computers in Human Behavior, 122, 106847. https://doi.org/10.1016/j.chb.2021.106847
Fang, G., Xu, X., Guo, J., Ying, Z., & Zhang, S. (2020). Identifiability of Bifactor Models. Statistica Sinica. http://www3.stat.sinica.edu.tw/ss_newpaper/SS-2020-0386_na.pdf
Wang, S., Zhang, S., & Shen, Y. (2020). A joint modeling framework of responses and response times to assess learning outcomes. Multivariate Behavioral Research, 55(1), 49-68. https://doi.org/10.1080/00273171.2019.1607238
