Kylie Gorney earned a B.S. in Psychology from the University of Wisconsin-Stout. She is continuing her studies in educational measurement and is working with Dr. James Wollack. Kylie's primary research interests include test security, item response theory, and latent variable models. She has served as a teaching assistant for two graduate-level educational statistics courses, and she is currently working as a research assistant at the National Conference of Bar Examiners (NCBE).
Mingya is a Ph.D. student working with Dr. David Kaplan. Her research interests lie in Bayesian approach, mixed-effects models, and large-scale assessment. More specifically, Bayesian model averaging, cross-random effects models, missing data in structural equation models as well as categorical data in the longitudinal study.
Qi Huang is a graduate student in Quantitative Methods area working with Professor Daniel M. Bolt. She earned her B.A. in English Literature from Peking University, and M.S. in Applied Statistics from Teachers College, Columbia University. Her research interests are item response theory (IRT) and Cognitive Diagnostic Models (CDMs).
Hanna Kim is a graduate student in the Quantitative Methods area. She received her B.A. in Education and M.A. in Educational Measurement and Evaluation at Seoul National University. Her research interests include propensity score analysis and Bayesian analysis with clustered data that are frequently used in education research. She is currently working as a project assistant at the Wisconsin Center for Educational Research (WCER) with Dr. Jee-Seon Kim.
My primary research interests are item response theory (IRT) and its applications to areas such as the measurement of non-cognitive traits. Other interests include hierarchical linear modeling, longitudinal data analysis, and test equating. I'm currently working as a Laboratory of Experimental Design (LED) TA in the Quantitative Methods area.
Ji-Seon Lee is a Ph.D. student in the Quantitative Methods area in Educational Psychology. She is currently studying educational statistics and working with Dr. Jee-Seon Kim. She received her B.A. in Business Administration from Sogang University. She also completed a B.A. in Education and a B.A. in Psychology and an M.A. in Measurement & Statistics in Psychology from Ewha Womans University.
Xiangyi Liao is a Ph.D. student in Quantitative Methods area in Educational Psychology Department. She received her B.A. in Economics from Southwestern University of Finance and Economics, and M.A. in Economics of Education from Peking University. She is currently working with Dr. Daniel Bolt. Her research interests are item response theory (IRT), test equating and linking. She is also interested in multilevel modeling and longitudinal data analysis.
Stan Lubanski is a graduate student in the Quantitative Methods area. Stan is interested in identifying the conditions where causal claims can be made (i.e., causal inference), especially randomized experiments and quasi-experimental designs.
Weicong Lyu is a Ph.D. student in the Quantitative Methods area. He is now studying educational measurement under Dr. Daniel Bolt. Weicong’s primary research interests are item response theory, Bayesian methods and causal inference.
Yiqin Pan is a Ph.D. student in Quantitative Methods Program. She earned a BS in Psychology and an MS in Psychometrics at Beijing Normal University. She is currently studying educational measurement and her advisor is James Wollack. Yiqin’s primary research interests are item response theory (IRT) and its applications to test security, specifically, detection of cheating on tests. Other interests include latent variable models and hierarchical linear modeling.
I am interested in the theory and application of psychometric methods (e.g., IRT and latent variable models) in education and psychology. I am working with Dr. James Wollack. My research focuses on (1) statistical modeling of anomalous testing taking behavior in educational and psychological measurement and (2) psychometric methodologies for the item- and person-level anomaly detection in the form of test collusion and item preknowledge as well as their potential to provide insight into valid and fair testing.
My research centers on multilevel modeling and causal inference. Also, I am interested in group-score assessment and analyzing timing and process data. I am currently working as a lecturer in ED PSY 763: Regression Models in Education.
I am a Ph.D. student working with Dr. David Kaplan. My primary interest is applying the Bayesian approach to educational research. More specifically, granting the model uncertainty and involving it into estimations on multiple imputation and multilevel datasets.
My current research focuses on the measurement of item-level response style effect from the perspective of multidimensional item response theory. I am also working as a project assistant at the UW Testing & Evaluation Center in Madison, WI. In addition to IRT, my research interests also extend to test equating and growth curve modeling.