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.
I will not admit new graduate students joining in Fall 2023.
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
Awards and Honors
Alicia Cascallar Award (NCME, 2022)
Excellent Reviewer Award (JEBS, 2021)
UIUC List of Teachers Ranked as Excellent by Students (SP 2021)
Courses Taught
- STAT 428
- PSYC 490
- Online workshop on Statistical Learning of Process Data (Video recording)
- Online workshop on R Programming for Data Science
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
Zhang, S., Wang, Z., Qi, J., Liu, J., & Ying, Z. (2021). Accurate Assessment via Process Data. https://arxiv.org/abs/2103.15034v1
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, 74(3), 427-464. 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., Wang, Z., Qi, J., Liu, J., & Ying, Z. (2021). Accurate Assessment via Process Data. https://arxiv.org/abs/2103.15034v1
