Yan Liu

Research Interests

My main research interests are in developing and disseminating innovative psychometric and statistical methods for addressing issues related to well-being and cognitive development. I have explored how we can apply causal models, including propensity score matching and mediation models, to psychometric and psychological research. I am also researching quantitative methods for analyzing response processes, longitudinal and multilevel data, and complex data, e.g., mixture distributions and zero-inflated distributions.

To analyze large scale assessment and text data, I have recently integrated machine learning and natural language processing (NLP) into my research. I also have been combining assessment and eye-tracking techniques into my studies on cognitive processes.

Selected Recent Journal Publications (* indicates student author):

Young, R., Domene, J. F., Liu, Y., Pradhan*, K. Botia*, A., & Chi*, E. (2025). Emotion in Career Related Transitions of Young Adults: A Contextual Action Perspective. Journal of Career Development, 0(0). DOI: 10.1177/08948453251382176

Hives*, B.A, Zumbo, B.D., Beauchamp, M. R., Liu, Y., Puterman, E. (2025). Bidirectional Week-to-Week Relationships Between Weekly Psychological Stress Across Multiple Life Domains and Engagement with an Exercise Intervention: Secondary Analysis of Data from a Randomized Trial. Annals of Behavioral Medicine, 59(1). DOI: 10.1093/abm/kaaf068

Waldhauser*, K. J., Hives, B. A., Liu, Y., Puterman, E., Sharifian, N., Castañeda, S. F., Carey, F. R., Rull, R. P., & Beauchamp, M. R., & the Millennium Cohort Study Team (2025). Military veterans’ psychological health and physical activity after separation from service. American Journal of Preventive Medicine, 69(2), 107642. DOI:10.1016/j.amepre.2025.04.012

Hives*, B. A., Beauchamp, M. R., Liu, Y., Weiss*, J., & Puterman, E. (2025). Multidimensional correlates of psychological stress: Insights from traditional statistical approaches and machine learning using a nationally representative Canadian sample. PLOS One,20(5): e0323197. DOI: 10.1371/journal.pone.0323197

Chen*, G., Tan*, B., Laham*, N., Tracey, T., Lapinski, S., & Liu, Y. (2025). A bibliometric review of natural language processing applications in psychology from 1991 to 2023. Basic and Applied Social Psychology, 47(2), 105–119. DOI: 10.1080/01973533.2024.2433720

Liu, Y., Maltais*, N., Milner-Bolotin, M., & Chachashvili-Bolotin, S. (2024). Investigating adolescent psychological well-being using PISA 2018 Canada data. Frontiers in Psychology, 15:1416631. DOI: 10.3389/fpsyg.2024.1416631

Laricheva*, M., Liu, Y., Shi*, E., & Wu, A. (2024). Scoping review on natural language processing applications in counselling and psychotherapy. British Journal of Psychology, 00, 1-25. DOI: 10.1111/bjop.12721

Young, R., Domene, J. F., Liu, Y., Pradhan*, K. Botia*, A., Chi*, E., Chiang*, M., Gendron*, M., Noel*, M., & Rosario*, S. (2024). The transition of young adult newcomers to Canada: Supporting participant joint projects. Journal of International Migration and Integration, 25(4), 2253-2271. DOI: 10.1007/s12134-024-01168-3

Liu, Y., Odic, D., Tang*, X., Ma*, A., Laricheva*, M., Chen*, G., Wu*, S., Niu*, M., Guo*, Y., & Milner-Bolotin, M. (2023). Effects of robotics education on young children’s cognitive development: A pilot study with eye-tracking. Journal of Science Education and Technology, 32, 295–308. DOI: 10.1007/s10956-023-10028-1

Liu, Y., Béliveau, A., Wei*, Y., Chen, M. Y., Record-Lemon, R., Kuo*, P., Pritchard*, E., Tang*, X., & Chen*, G. (2022). A gentle introduction to Bayesian network meta-analysis using an automated R Package. Multivariate Behavioral Research, 58(4), 706-722. DOI: /10.1080/00273171.2022.2115965

Liu, Y., Laricheva*, M., Zhang*, C., Boutet*, P., Chen*, G., Tracy, T., Carenini, G., & Young, R. (2022). Transition to adulthood for young people with intellectual or developmental disabilities: Emotion detection and topic modeling. In Thomson, R., Dancy, C., Pyke, A. (eds) Social, cultural, and behavioral modeling. SBP-BRiMS 2022. Lecture Notes in Computer Science, vol 13558. Springer, Cham. DOI: 10.1007/978-3-031-17114-7_21

Laricheva*, M., Zhang*, C., Liu, Y., Chen*, G., Tracy, T., Carenini, G., & Young, R. (2022). Automated utterance labeling of conversations using natural language processing. In Thomson, R., Dancy, C., Pyke, A. (eds) Social, cultural, and behavioral modeling. SBP-BRiMS 2022. Lecture Notes in Computer Science, vol 13558. Springer, Cham. DOI: 10.1007/978-3-031-17114-7_23

Liu, Y., Béliveau, A., Besche, H. C., Wu, D. A., Zhang, X. Y., Stefan, M., Gutlerner, J., & Kim, C. (2021). Bayesian mixed effects model and data visualization for understanding item response time and response order in an open online assessment. Frontiers in Education: Assessment, Testing and Applied Measurement, 5:607260. DOI: 10.3389/feduc.2020.607260

Beauchamp, M. R., Liu, Y., Ruissen*, G. R., Hulteen, R. M., Rhodes, R. E., & Faulkner, G. (2021). Psychological mediators of exercise adherence among older adults in a group-based randomized trial. Health Psychology, 40(3), 166-177. DOI: 10.1037/hea0001060

Liu, Y., Kim, C., Wu, A. D., Gustafson, P., Kroc, E., & Zumbo, B. D. (2020). Investigating the performance of propensity scores approaches for differential item functioning analysis. Journal of Modern Applied Statistical Methods, 18(1), eP274. DOI: 10.22237/jmasm/1556669280