معرفی
Dr. Johnson Li serves as Associate Professor in the Department of Psychology, Faculty of Arts at the University of Manitoba, where he chairs the Quantitative Methods section of the Canadian Psychological Association. His academic journey spans institutions including the University of Alberta, Chinese University of Hong Kong, and University of Hong Kong.
His educational background includes:
- PhD (Measurement, Evaluation, and Cognition) from University of Alberta
- M.Phil (Psychology) from Chinese University of Hong Kong
- BSSc (Psychology) from University of Hong Kong
Dr. Li's research pioneers robust statistical methodologies for psychological measurement, focusing on effect size estimation, scale validation, and correction techniques for non-normal data and range restriction. His work bridges theoretical psychometrics with practical applications in educational and organizational settings, emphasizing reliability and validity in measurement models.
Analysis of his publication record reveals consistent innovation in robust statistics, particularly through bootstrap methods and probability-based effect sizes. His research addresses critical methodological gaps in handling outliers, heteroscedasticity, and multivariate relationships across psychological subfields.
His scientific recognition includes:
- Terry G. Falconer Memorial Emerging Researcher Award (2019)
- Department of Psychology Teaching Award (2016)
- Faculty of Arts Special Achievements Award (2016)
Dr. Li actively mentors Master's and PhD students in data analysis and research methodology while teaching core quantitative courses including PSYC 7200/7210. His leadership extends to developing statistical resources through the Quantitative and Applied Statistics (LIQAS) lab.
The LIQAS lab provides open-access R packages and computational tools for robust correlations, common-language effect sizes, and probability-based statistics, serving as a vital resource for methodological advancement in behavioral sciences.
