Dan Su is a PhD student in Quantitative Methods Program, Department of Educational Psychology. She received her Master’s degree in Quantitative Methods and Minor in Statistics in 2014. She worked on the design and analysis of vignette experiments (factorial surveys) in her Master’s Thesis. For her dissertation, she received the AERA dissertation grant award on planned missing data designs for causal inference in large-scale assessments (e.g., PISA). Her general research interests include planned missing data designs in large surveys, imputation methods for missing data, experimental designs for factorial surveys, and causal inference with the Rubin causal model and graphic models. Besides studying quantitative methodology, she is also a contemporary dancer and choreographer.
Ph.D. (Quantitative Methods), University of Wisconsin-Madison, 2018
M.S. (Quantitative Method, Minor in Statistics), University of Wisconsin-Madison, 2014
B.A. (Management Science), Sichuan University, China, 2012
Su, D. & Steiner, P. M. (forthcoming). An evaluation of experimental designs for constructing vignette sets in factorial surveys. Sociological Methods & Research.
Kaplan, D. & Su, D. (2016). On matrix sampling and imputation of context questionnaires with implications for the generation of plausible values in large-scale assessments. Journal of Educational and Behavioral Statistics. doi: 10.3102/1076998615622221
Steiner, P. M., Atzmüller, C., & Su, D. (2016). Designing valid and reliable vignette experiments for survey research: A case study on the fair gender income gap. Journal of Methods and Measurement in the Social Sciences, 7(2), 52-94.
Steiner, P. M., Kim, Y., Hall, C. E. & Su, D. (2015). Graphical models for quasi-experimental designs. Sociological Methods & Research, doi: 0049124115582272