Guanglei Hong obtained a Master's degree in Statistics and a Ph.D. in Education from the University of Michigan in 2004. She is the Inaugural Chair of the University-wide Committee on Quantitative Methods in Social, Behavioral, and Health Sciences (https://qrm.uchicago.edu/) and a member of the Committee on Education (https://voices.uchicago.edu/coed/) at the University of Chicago. Before joining the University of Chicago faculty in July 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.
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 issues in the social sciences, Professor Hong communicates with a broad audience through studies of specific research questions in education and beyond. Her book “Causality in a social world: Moderation, mediation, and spill-over” was published in July 2015 (https://voices.uchicago.edu/ghong/test-page/).
Her research has received support from the National Science Foundation, the Spencer Foundation, the National Academy of Education, the William T. Grant Foundation, the US Department of Education Institute of Education Sciences, and the Social Sciences and Humanities Research Council of Canada.
She teaches quantitative methods courses including Applied Statistics in Human Development Research, Introduction to Causal Inference, and Mediation, Moderation, and Spillover Effects.
Hong, G. (2015). Causality in a social world: Moderation, mediation, and spill-over. West Sussex, UK: Wiley-Blackwell.
Hong, G. (2012). Journal of Research on Educational Effectiveness special issue on the statistical approaches to studying mediator effects in education research. (Guest Editor)
Qin, X., Hong, G., Deutsch, J., & Bein, E. (forthcoming). Multisite causal mediation analysis in the presence of complex sample and survey designs and non-random nonresponse. Journal of the Royal Statistical Society, Series A.
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.
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), 222-244.
Hong, G., Deutsch, J., & Hill, H. D. (2015). Ratio-of-mediator-probability weighting for causal mediation analysis in the presence of treatment-by-mediator interaction. Journal of Educational and Behavioral Statistics, 40(3), 307-340.
VanderWeele, T., Hong, G., Jones, S., & Brown, J. (2013). Mediation and spillover effects in group-randomized trials: A case study of the 4R’s educational intervention. Journal of the American Statistical Association, 108(502), 469-482.
Hong, G., Raudenbush, S. W. (2013). Heterogeneous agents, social interactions, and causal inference. In the Handbook of Causal Analysis for Social Research (pp.331-352) edited by Stephen L. Morgan. NY: Springer.
Hong, G., & Nomi, T. (2012). Weighting methods for assessing policy effects mediated by peer change. Journal of Research on Educational Effectiveness special issue on the statistical approaches to studying mediator effects in education research, 5(3), 261-289.
Hong, G. (2012). Marginal mean weighting through stratification: A generalized method for evaluating multi-valued and multiple treatments with non-experimental data. Psychological Methods, 17(1), 44-60.
Hong, G., Corter, C., Hong, Y., & Pelletier, J. (2012). Differential effects of literacy instruction time and homogeneous grouping in kindergarten: Who will benefit? Who will suffer? Educational Evaluation and Policy Analysis. 34(1), 69-88.
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. (2010). Ratio of mediator probability weighting for estimating natural direct and indirect effects. In JSM Proceedings, Biometrics Section. Alexandria, VA: American Statistical Association, pp.2401-2415.
Hong, G., & Hong, Y. (2009). Reading instruction time and homogeneous grouping in kindergarten: An application of marginal mean weighting through stratification. Educational Evaluation and Policy Analysis, 31(1), 54-81.
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., & Yu, B. (2008). Effects of kindergarten retention on children’s social-emotional development: An application of propensity score method to multivariate multi-level data. Special Section on New Methods in Developmental Psychology, 44(2), 407-421.
Hong, G., & Yu, B. (2007). Early grade retention and children’s reading and math learning in elementary years. Educational Evaluation and Policy Analysis, 29(4), 239-261.
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.
William T. Grant Scholar, William T. Grant Foundation, 2009-2014
NAE/Spencer Postdoctoral Fellowship, National Academy of Education and Spencer Foundation, 2006-2007
AERA Mary Catherine Ellwein Outstanding Dissertation Award – Measurement and Quantitative Research Methodology, American Educational Research Association, Division D, 2005
Spencer Dissertation Fellowship for Research Related to Education, Spencer Foundation, 2003-2004
Joint Statistical Meetings Student Paper Competition Award, American Statistical Association, 2003
AERA Dissertation Grant, American Educational Research Association, 2002-2003