Xu Qin

PhD
  • Assistant Professor, Health and Human Development
  • Assistant Professor, Biostatistics

I am an Assistant Professor of Research Methodology at the School of Education (primary) and an Assistant Professor of Biostatistics at the School of Public Health (secondary). My research focuses on solving cutting-edge methodological problems in causal mediation analysis and multilevel modeling. I am also interested in using rigorous and innovative quantitative methods to evaluate the impacts of interventions and the underlying mechanisms.

Methodologically, I have developed statistical methods and software for investigating the heterogeneity in causal mediation mechanisms in both multilevel and single-level settings, as well as sensitivity analysis and power analysis methods for causal mediation analysis. Substantively, I am interested in applying advanced causal mediation analysis methods in developmental, health, and educational research.
 

Education

2018 | University of Chicago, Chicago, IL | PhD, Quantitative Methods in Education and Human Development
2012 | Renmin University of China, Beijing, China | Master, Statistics
2010 | Renmin University of China, Beijing, China | Bachelor, Statistics

Teaching

EFOP 2410 Applied Regression Analysis | Fall 2018, Fall 2019, Fall 2020, Fall 2021

EFOP 3408 Hierarchical Linear Modeling | Spring 2019, Spring 2020, Spring 2021, Spring 2022

Selected Publications
‡ PhD student advisee
 
  • Qin, X. (conditionally accepted). Introduction to Causal Mediation Analysis. Asia Pacific Education Review. (Invited paper for a special issue on Causal Research Designs and Analysis in Education.)
     
  • Qin, X. (in press). Sample Size and Power Calculations for Causal Mediation Analysis. Behavior Research Methods.
     
  • Qin, X. & Wang, L. (in press). Causal Moderated Mediation Analysis: Methods and Software. Behavior Research Methods.
  • Hong, G., Yang, F., & Qin, X. (in press). Post-Treatment Confounding in Causal Mediation Studies: A Cutting-Edge Problem and A Novel Solution via Sensitivity Analysis. Biometrics.
     
  • ‡ Guzman-Alvarez, A., Qin, X., & Scott, P. (in press). Deep neural networks for propensity score estimation (abstract), Multivariate Behavioral Research.  (* Funded by 2021 NAEd/Spencer Dissertation Fellowship awarded to the first author, Ph.D. mentee)
  • Park, S., Qin, X., & Lee, C. (in press). Estimation and sensitivity analysis for causal decomposition analysis in disparity research. Sociological Methods and Research.
     
  • Qin, X. & Yang, F. (in press). Simulation-based sensitivity analysis for causal mediation studies. Psychological Methods.
     
  • Wang, M.-T., Zepeda, C., Qin, X., Del Toro, J., & Binning, K. R. (2021). More than growth mindset: individual and interactive links among socioeconomically disadvantaged adolescents’ ability mindsets, metacognitive skills, and math engagement. Child Development, 92(5), e957-e976.
     
  • Qin, X., Wormington, S., ‡ Guzman-Alvarez, A., & Wang, M.-T. (2021). Why does a growth mindset intervention impact achievement differently across secondary schools? Unpacking the mediation mechanism from a national multisite randomized experiment. The Journal of Research on Educational Effectiveness, 14(3), 617-644.
     
  • Wang, M.-T., Binning, K. R., Del Toro, J., Qin, X., & Zepeda, C. (2021). Skill, thrill, and will: The role of metacognition and motivation in predicting student engagement over time. Child Development, 92(4), 1369-1387(Del Toro and Qin had equal intellectual contribution)
     
  • Qin, X., Deutsch, J, & Hong, G. (2021). Unpacking complex mediation mechanisms and their heterogeneity between sites in a Job Corps evaluation. The Journal of Policy Analysis and Management, 40(1), 158-190.
     
  • Hong, G., Yang, F., & Qin, X. (2021). Did you conduct a sensitivity analysis? A new weighting-based approach for evaluations of the average treatment effect for the treated. Journal of the Royal Statistical Society, Series A (Statistics in Society), 184(1), 227-254.
     
  • Qin, X., Hong, G., Deutsch, J, & Bein, E. (2019). Multisite causal mediation analysis in the presence of complex sample and survey designs and non-random nonresponse. The Journal of the Royal Statistical Society, Series A (Statistics in Society), 182(4), 1343-1370.
     
  • Hong, G., Qin, X., & Yang, F. (2018). Weighting-based sensitivity analysis in causal mediation studies. Journal of Educational and Behavioral Statistics, 43(1), 32-56.
     
  • Bein, E., Deutsch, J., Hong, G., Porter, K., Qin, X., & Yang, C. *(2018). Two-step estimation in rmpw analysis. Statistics in Medicine, 37(8), 1304-1324.
     
  • Qin, X., & Hong, G. (2017). A weighting method for assessing between-site heterogeneity in causal mediation mechanism. Journal of Educational and Behavioral Statistics, 42(3), 308-340.
Department/Affiliation