Department of Comparative Human Development
Guanglei Hong is a Professor of Comparative Human Development. Dr. Hong develops and applies causal inference theories and methods for evaluating educational and social policies and programs in multi-level, longitudinal settings. Her work is currently focused on developing concepts and methods for analyzing causal mediation mechanisms, for revealing spillover effects, and for conducting sensitivity analysis. Because advancements in these quantitative research methods can be put to highly impactful use through empirical investigations of prominent policy issues, Professor Hong communicates with a broad audience through studies of specific policies and practices in education and beyond. This research has received support from the Social Sciences and Humanities Research Council of Canada, the Spencer Foundation, the National Academy of Education, the William T. Grant Foundation, and the US Department of Education Institute of Education Sciences among other sources of funding. Professor Hong is the recipient of a 2003 Joint Statistical Meetings Student Paper Competition Award, a 2003 Spencer Dissertation Fellowship, a 2005 AERA Division D Outstanding Dissertation Award, a 2006 National Academy of Education/Spencer Postdoctoral Fellowship, and a 2009-2014 William T. Grant Foundation Scholars Award. Her book “Causality in a social world: Moderation, mediation, and spill-over” was published in July 2015. Professor Hong obtained a Master’s degree in Applied Statistics and a Ph.D. in Education from the University of Michigan in 2004. Before joining the University of Chicago faculty in 2009, she had been an Assistant Professor in the Human Development and Applied Psychology Department in the Ontario Institute for Studies in Education of the University of Toronto.
Selected Recent Publications
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-
Garrett, R., & Hong, G. (2016). Impacts of grouping and time on the math learning of
language minority kindergartners. Educational Evaluation and Policy Analysis, 38(2), 222-
Hong, G. (2010). Marginal mean weighting through stratification: Adjustment for selection bias in multilevel data. Journal of Educational and Behavioral Statistics, 35(5), 499-531.
Hong, G., & Raudenbush, S. W. (2008) Causal inference for time-varying instructional treatments. Journal of Educational and Behavioral Statistics, 33(3), 333-362.
Hong, G., & Raudenbush, S. W. (2006). Evaluating kindergarten retention policy: A case study of causal inference for multi-level observational data. Journal of the American Statistical Association, 101(475), 901-910.
Hong, G., & Raudenbush, S. W. (2005). Effects of kindergarten retention policy on children’s cognitive growth in reading and mathematics. Educational Evaluation and Policy Analysis, 27(3), 205-224.