- Li, J. C.-H. (2024). Incorporating modern robust statistical methods into graduate teaching. Teaching and Learning Symposium, University of Manitoba (May 16)
- Li, J. C.-H. (2024). The role of Monte Carlo Simulation in advancing quantitative methods in psychology with violation of data assumptions. Social Science Speaker Series. Centre for Social Sciences Research and Policy, University of Manitoba. (March 15)
- Li, J. C.-H. (2024). What could you do when data violate assumptions (e.g., normality) for common quantitative data analyses? The role of robust statistics in psychological research. Research Seminar, Oxford Brookes University, the U.K. (April 10)
- Li, J. C.-H. (2021). Using the probability-of-superiority approach to fit latent variable models. Symposium presented at the Statistical Society of Canada Convention (June 8)
- Li, J. C.-H. (2017). Latent variable modeling in behavioral and social sciences. Department of Economics, University of Manitoba. (February 10)
- Li, J. C.-H. (2017). Simulated Statistician: Engaging social sciences students in learning statistics. Teaching and Learning Symposium, University of Manitoba (October 16)
- Li, J C.-H. (2014). Bootstrap confidence intervals for correlations adjusted for range restriction – a popular data analytic technique in educational and employment selection. Department of Statistics, University of Manitoba (October 17)
- Li, J C.-H. (2014). How to deal with “restricted range” when estimating validity in psychological research?Learning Analytics Summer Institute (LASI) – Hong Kong meeting. Hong Kong, China. (July 4).
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