Embedded Files
Biosketch
Biosketch
Beginning in January 2025, I will be an Associate Professor with the Quantitative Psychology specialization in the Department of Psychology at UC Riverside. My research and teaching interests include methodological investigations and applications in statistical modeling and data science, with my work focusing on longitudinal structural equation models, zero-inflated generalized linear models, mediation analysis, and data-driven approaches to constructing models. My methodological work is informed by applied issues in the behavioral sciences, particularly the areas of health, substance use, and cognitive neuroscience. In my free time I enjoy volunteering with Statistics Without Borders. On this site you can find information on my papers, courses, and software files.
Topics I Teach
Topics I Teach
Mediation Analysis
Structural Equation Modeling
General Linear Modeling (includes topics in multiple regression, ANOVA, and correlation)
Introductory Statistics
Selected methodological publications
Selected methodological publications
(Full CV here)
O’Rourke, H. P., & Han, D. E. (2023). Considering the distributional form of zeroes when calculating mediation effects with zero-inflated count outcomes. Journal of Behavioral Data Science, 3(2), 1-14. https://doi.org/10.35566/jbds/v3n2/orourke
O’Rourke, H. P., Fine, K. L., Grimm, K. J., & MacKinnon, D. P. (2022). The importance of time metric precision when implementing bivariate latent change score models. Multivariate Behavioral Research, 57, 561-580. https://doi.org/10.1080/00273171.2021.1874261
Hilley, C. D., & O’Rourke, H. P. (2022). Dynamic change meets mechanisms of change: Mediation in the latent change score framework. International Journal of Behavioral Development, 46, 125-141. https://doi.org/10.1177/01650254211064352
Grimm, K. J., Helm, J., Rodgers, D., & O’Rourke, H. P. (2021). Analyzing cross-lag effects: A comparison of different cross-lag modeling approaches. New Directions for Child and Adolescent Development, 175, 11-33. https://doi.org/10.1002/cad.20401
O’Rourke, H. P., & Vazquez, E. (2019). Mediation analysis with zero-inflated substance use outcomes: Challenges and recommendations. Addictive Behaviors, 94, 16-25. https://doi.org/10.1016/j.addbeh.2019.01.034
O’Rourke, H. P., & MacKinnon, D. P. (2019). The importance of mediation analysis in substance-use prevention. In Z. Sloboda, H. Petras, E. Robertson, & R. Hingson (Eds.), Prevention of Substance Use (pp. 233-246). Cham, Switzerland: Springer Nature.
O’Rourke, H. P., & MacKinnon, D. P. (2018). Reasons for testing mediation in the absence of an intervention effect: A research imperative in prevention and intervention research. Journal of Studies on Alcohol and Drugs, 79, 171-181. https://doi.org/10.15288/jsad.2018.79.171
Gonzalez, O., O’Rourke, H. P., Wurpts, I. C., & Grimm, K. J. (2018). Analyzing Monte Carlo simulation studies with classification and regression trees. Structural Equation Modeling, 25, 403-413. https://doi.org/10.1080/10705511.2017.1369353
Miočević, M., O’Rourke, H. P., MacKinnon, D. P., & Brown, C. H. (2018). Statistical properties of four effect-size measures for mediation models. Behavior Research Methods, 50, 285-301. https://doi.org/10.3758/s13428-017-0870-1
O’Rourke, H. P., & MacKinnon, D. P. (2015). When the test of mediation is more powerful than the test of the total effect. Behavior Research Methods, 47, 424-442. https://doi.org/10.3758/s13428-014-0481-z
Report abuse