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:
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Latent variable modeling: missing data, response times, diagnostic classification, Bayesian estimation;
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Longitudinal models for learning and interventions;
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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
Grants
IES R324P210005 (co-PI): Analysis of NAEP Mathematics Process, Outcome, and Survey Data to Understand Test-Taking Behavior and Mathematics Performance of Learners with Disabilities
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
Guo, J., Xu, X., Ying, Z., & Zhang, S. (2021). Modeling Not-Reached Items in Timed Tests: A Response Time Censoring Approach. Psychometrika. https://doi.org/10.1007/s11336-021-09810-0
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
Guo, J., Xu, X., Ying, Z., & Zhang, S. (2021). Modeling Not-Reached Items in Timed Tests: A Response Time Censoring Approach. Psychometrika. https://doi.org/10.1007/s11336-021-09810-0
Tang, X., Zhang, S., Wang, Z., Liu, J., & Ying, Z. (Accepted/In press). ProcData: An R Package for Process Data Analysis. Psychometrika. https://doi.org/10.1007/s11336-021-09798-7
Zhang, S. (2021, Mar 28). Accurate Assessment via Process Data.
