Johnson Li

• PSYC 2260 - Introduction to Research Methods in Psychology
• PSYC 3200 - Thinking critically about psychological research
• PSYC 3340 - Design and analysis for psychological experiments
• PSYC 7200 - Quantitative methods in psychology I
• PSYC 7210 - Quantitative methods in psychology II
• PSYC 7400 - Measurement and scaling theory

Dr. Johnson Li started his research in quantitative methods when he studied his Master of Philosophy at the Chinese University of Hong Kong, and he conducted and published a study that could handle and adjust the bias of behavioural data that is subject to restriction of range, a common phenomenon where the range of variability of the scores have been restricted because of some section procedures (e.g., college admission, job selection). He further extended his research to psychological and educational measurement through his Ph.D. study at the University of Alberta, and he collaborated with his peers and researchers in advancing measurement models such as cognitive diagnostic modelling, computer-adaptive testing, and item response theory. He started his tenure-track assistant professorship position in the Faculty of Education at the University of Hong Kong when he graduated from his Ph.D. program and later joined the psychology department at the University of Manitoba. His role includes conducting research in advancing research and quantitative methods in psychology, advising students in data analysis and interpretation, and teaching undergraduate and graduate design and methods courses in psychology. He is currently taking the role as an Associate Professor and serving as the Chair of the Quantitative Methods (QM) section of the Canadian Psychological Association (CPA).

• PhD (Measurement, Evaluation, and Cognition), University of Alberta
• M Phil (Psychology), Chinese University of Hong Kong
• BSSc (General) - Psychology, University of Hong Kong

Research interests

• Developing mathematical and statistical methods in psychology
• Design of research studies
• Educational and psychological measurement
• Application of statistical models
• Scale development and validation

Research summary

Dr. Johnson Li's research topics include, but are not limited to, effect size estimates, resampling techniques, statistical correction for study artifacts, creation and evaluation of educational and psychological scales, meta-analysis, robust statistics , probability-based statistics, structural equation modelling, cognitive diagnostic modelling, and reliability and validity assessments.

• Li, J. C.-H. (2022). Bootstrap confidence intervals for 11 robust correlations in the presence of outliers and leverage observations. Methodology, 18(2), 99-125. 
• Li, J. C.-H., & Tze, V. M. C. (2021). Analytic and bootstrap confidence intervals for the common-language effect size estimate. Methodology, 17, 1-21. doi:10.5964/meth.4495
• Li, J. C.-H., Nesca, M., Waisman, R., Cheng, Y., & Tze, V. M. (2021). A robust effect size for MANOVA with non-normal and non-homogenous data. Methodological Innovations, 14, 3. 
• Li, J. C.-H., & Waisman, R. (2019). Probability of bivariate superiority: A non-parametric common-language statistic for detecting bivariate relationships. Behavior Research Methods, 51, 258-279. doi:10.3758/s13428-018-1089-5. 
• Li, J. C.-H., & Tze, V. M. C. (2019). Moderation in lifespan developmental analyses. Oxford Research Encyclopedia of Psychology. Oxford University Press. doi:10.1093/acrefore/9780190236557.013.35
• Li, J. C.-H. (2018). Probability-of-superiority SEM (PS-SEM)—Detecting probability-based multivariate relationships in behavioral research. Frontiers in Psychology, 9:883. doi:10.3389/fpsyg.2018.00883. 
• Li, J. C.-H. (2018). Curvilinear moderation—A more complete examination of moderation effects in behavioral sciences. Frontiers in Applied Mathematics and Statistics, 4:7, doi:10.3389/fams.2018.00007
• Li, J. C.-H. (2016). Effect size measures in a two independent-samples case with non-normal and non-homogeneous data. Behavior Research Methods, 48, 1560-1574. doi:10.3758/s13428-015-0667-z. 
• Li, J. C.-H. (2015). Cohen’s d corrected for Case IV range restriction: A more accurate procedure for evaluating group differences in organizational research. Personnel Psychology, 68, 899-927. doi:10.1111/peps.12096. 
• Li, J. C.-H., Cui, Y., & Chan, W. (2013). Bootstrap confidence intervals for the mean correlation corrected for Case IV range restriction - A more adequate procedure for meta-analysis. Journal of Applied Psychology, 98, 183-193. doi:10.1037/a0029946. 
   

• 2019 - The Terry G. Falconer Memorial Emerging Researcher Award, Winnipeg Research Institute Foundation, Manitoba, Canada
• 2016 - Department of Psychology Teaching Award, University of Manitoba
• 2016 - Special Achievements Award, Faculty of Arts, University of Manitoba