My name is Ruoxuan (Roxanne) Li. Currently, I am a fourth-year Ph.D. student in Quantitative Psychology program at the University of Notre Dame, where I have been studying since 2021. I am current under supervision of Prof. Lijuan (Peggy) Wang at University of Notre Dame. I also work close with Prof. Irene J. K. Park at Indiana University School of Medicine, Prof. Margarita Alegría at Harvard Medical School, and Prof. Tiffany Yip at Fordham University.

Research Interests

My research interests are focused on the application of advanced statistical methods and machine learning techniques in psychology. Specifically, I have been working on dynamic structural equation models, causal inference, and the development of predictive models using deep learning. I am passionate about exploring how these methodologies can enhance our understanding of psychological processes and improve interventions in educational and health settings.

Currently, my work encompasses both methodological and empirical studies. Methodologically, I am interested in developing new methods within the structural equation modeling framework and comparing longitudinal models in mediation analysis. Empirically, I explore adolescents’ development, including studies on discrimination and distress, as well as industry and organizational topics such as employees’ motivational dynamics and teachers’ turnover intentions.

Education

🎒 2021 - Now, Ph.D. Quantitative Psychology, University of Notre Dame, Notre Dame, IN, USA

🎓 2021 - 2024, M.S. Applied Statistics, University of Notre Dame, Notre Dame, IN, USA

🎓 2017 - 2020, M.A. School and Education Psychology, Beijing Normal University, Beijing, China

🎓 2017 - 2020, B.S. Psychology, Beijing Normal University, Beijing, China

Honors and Awards

• Outstanding Graduate Student TA Awards, University of Notre Dame, 2024
• National Scholarship（Top 0.2%）in recognition of outstanding academic performance, China, 2018 and 2019

Selected Publications

• Park, I. J., Wang, L., Li, R., Yip, T., Valentino, K., Cruz‐Gonzalez, M., … & Alegría, M. (2024). A daily diary study of discrimination and distress in Mexican‐origin adolescents: Testing mediating mechanisms. Child Development, 1-16.
• Li, R., & Wang, L. (2024). Investigating weight constraint methods for causal-formative indicator modeling. Behavior Research Methods, 1-13.
• Li, R., & Wang, L. (2024). An Analytical Comparison of Three Modeling Approaches for Longitudinal Mediation Analysis. Multivariate Behavioral Research, 1-3.
• Li, R., & Wang L. An analytical comparison of three modeling approaches for longitudinal mediation analysis [Abstract]. Multivariate Behavioral Research.
• Li, R., Liu, H., Chen, Z., & Wang Y. (2023). Dynamic and cyclic relationships between employee’s intrinsic and extrinsic motivations: The evidence from dynamic multilevel modeling analysis. Journal of Vocational Behavior, 140, 103813. doi:10.1016/j.jvb.2022.103813
• Li, R. (2023). Robust Bayesian growth curve modeling: A tutorial using JAGS. Journal of Behavioral Data Science, 3, 1-21. doi: 10.35566/jbds/v3n2/li
• Li, R., & Yao., M. (2022). What promotes teachers’ intention to leave? Evidence from a meta-analysis. Educational Research Review, 37, 100477. doi: 10.1016/j.edurev.2022.100477
• Li, R., Liu, H., Chen, Y, & Yao, M. (2022). Teacher engagement and self-efficacy: The mediating role of continuing professional development and moderating role of teaching experience. Current Psychology, 41, 328-37. doi: 10.1007/s12144-019-00575-5.
• Li, R., Liu, H., Chen, Y., & Yao, M. (2021). Why teachers want to leave? The roles of achievement goals, burnout and perceived school context. Learning and Individual Differences, 89, 102032. doi: 10.1016/j.lindif.2021.102032
• Li, R., Chen, Y., Liu, H., & Yao, M. (2020). Need satisfaction and frustration profiles: Who benefits more on social networking sites? Personality and Individual Differences, 152, 109854. doi: 10.1016/j.paid.2020.109854
• Li, R., Yao, M., Chen, Y, & Liu, H. (2020). Parent autonomy support and psychological control, Dark Triad, and subjective well-being of Chinese adolescents: Synergy of variable- and person-centered approaches. The Journal of Early Adolescence, 40, 966-995. doi: 10.1177/0272431619880335.
• Li, R., Yao, M., Liu, H., & Chen, Y. (2019). Chinese parental involvement and adolescent learning motivation and subjective well-being: More is not always better. Journal of Happiness Studies, 21, 2527-2555. doi: 10.1007/s10902-019-00192-w
• Li, R., Yao, M., Liu, H., & Chen, Y. (2019). Relationships among autonomy support, psychological control, coping, and loneliness: Comparing victims with nonvictims. Personality and Individual Differences, 138, 266–272. doi: 10.1016/j.paid.2018.10.001.
• Li, R.*, Liu, H.*, Yao, M., & Chen, Y. (2019). Regulatory focus and subjective well-being: The mediating role of coping styles and the moderating role of gender. The Journal of Psychology, 153, 714-731. doi: 10.1080/00223980.2019.1601066. (* = equal contribution).

Selected Talks

• Li, R., & Wang, L. (2024). Comparing three approaches for modeling data with ceiling or floor effects. Oral presentation at 2024 International Meeting of Psychometric Society (IMPS). Prague, Czech Republic.
• Li, R., & Wang, L. (2023). Investigating weight constraint methods for modeling causal-formative indicators. Oral presentation at 2023 International Meeting of Psychometric Society (IMPS). College Park, Maryland, United States.
• Li, R., & Wang, L. (2023). An analytical comparison of the cross-lagged, latent growth curve, and latent difference score models for longitudinal mediation analysis. Poster presentation at Society of Multivariate Experimental Psychology 2023 Program. Iowa City, Iowa, United States.
• Li, R., Chen, Y., Liu, H., & Yao, M. (2019). Need satisfaction and frustration profiles and their relations with SNSs outcomes: A person-centered approach. Oral presentation at the XVI European Congress of Psychology. Moscow State University, Russia.

Service

I have served as a reviewer for more than 20 peer-reviewed journals, including:

• Journal of Happiness Studies
• Public Health
• Social Science Computer Review
• Journal of Child and Family Studies
• Behavior & Information Technology
• Current Psychology
• BMC Psychology
• Journal of School Violence

Teaching

2024 and 2023 Spring, Behavior Science, Teaching Assistant