Gyeongcheol Cho is an assistant professor in the Psychology Department at The Ohio State University. He earned his B.A. in economics with a minor in mathematics from Korea University in South Korea in 2017 and obtained his Ph.D. in Quantitative Psychology from McGill University in Canada in 2023. His research is devoted to advancing quantitative methods to explore and confirm the intricate relationships that exist between human behavioral, psychological, and biological variables, with a special emphasis on the measurement of theoretical constructs. From a technical standpoint, his research encompasses factor/component analyses, structural equation modeling, and interpretable machine learning.

Awards and Honors

• 2025: Anne Anastasi Dissertation Award, American Psychological Association Division 5 (Quantitative and Qualitative Methods)
• 2024: Best Paper Award, International Society for Data Science and Analytics
• 2024: Dissertation Prize, Psychometric Society
• 2022: Quantitative Methods Research Award, Quantitative Methods Section, Canadian Psychological Association 
• 2021: Most Popular Paper Award, Journal of Marketing Analytics
• 2018: Grand Prize for Poster, Korean Society of Psychological Measurement and  Assessment
• 2017 – 2023: McGill Graduate Studies Fellowship, Psychology, McGill University
• 2013: Honor Scholarships, Korea University

Select Publications

• Cho, G., Sarstedt, M., & Hwang, H (2022). A comparative evaluation of factor- and component-based structural equation modeling methods under (in)consistent construct representations. British Journal of Mathematical and Statistical Psychology, 75(2), 220-251.
   
• Cho, G.^*, & Hwang, H. (2023). Structured factor analysis: A data matrix-based alternative approach to structural equation modeling, Structural Equation Modeling: A Multidisciplinary Journal, 30(3), 364-377.
   
• Cho, G., & Hwang, H (2023). Deep learning generalized structured component analysis: An interpretable artificial neural network model with composite indexes, Structural Equation Modeling: A Multidisciplinary Journal Multivariate Behavioral Research. Advance online publication
   
• Hwang, H., Cho, G., Jin, M. J., Ryoo, J. H., Choi, Y., & Lee, S. H. (2021). A knowledge-based multivariate statistical method for examining gene-brain-behavioral/cognitive relationships: Imaging genetics generalized structured component analysis. PloS One, 16(3), e0247592.
   
• Hwang, H., Cho, G., Jung, K., Falk, C., Flake, J., Jin, M., & Lee, S. H. (2021). An approach to structural equation modeling with both factors and components: Integrated generalized structured component analysis. Psychological Methods, 26(3), 273–294.

View additional publications in our faculty research database →