Structural Equation Modeling, Latent Variable Modeling, Bayesian Analysis
Related Faculty
- Mantey, D. S., Yockey, R. A., & Springer, A. E. (2023). Digital screen time and suicidality during high school: How important is cyberbullying? A mediation analysis using the youth risk behavioral surveillance survey, 2011–2019. Preventive medicine, 166, 107330.
- Yockey, R. A., Brown, J. L., Littlefield, A. K., & Talley, A. E. (2020). Self-esteem, Acculturative Stress, and Marijuana Use Among Hispanic College Students. Hispanic Journal of Behavioral Sciences, 42(3), 416-425.
- Huh, D., Li, X., Zhou, Z., Walters, S. T., Baldwin, S. A., Tan, Z., … & Mun, E. Y. (2022). A structural equation modeling approach to meta-analytic mediation analysis using individual participant data: Testing protective behavioral strategies as a mediator of brief motivational intervention effects on alcohol-related problems. Prevention Science, 23(3), 390-402.
- Kim, S.-Y., Mun, E.-Y., & Smith, S. S. (2014). Using mixture models with known class membership to address incomplete covariance structures in multiple-group growth models. British Journal of Mathematical and Statistical Psychology, 67(1), 94-116.
- Kim, S.-Y., Huh, D., Zhou, Z., & Mun, E.-Y. (2020). A comparison of Bayesian to maximum likelihood estimation for latent growth models in the presence of a binary outcome. International Journal of Behavioral Development, 44(5), 447-457.
- Mun, E.-Y., von Eye, A., & White, H. R. (2009). An SEM approach for the evaluation of intervention effects using pre-post-post designs. Structural Equation Modeling, 16(2), 315-337.
- Tan, Z., Mun, E.-Y., Nguyen, Uyen-Sa, D. T., & Walters, S. T. (2021). Increases in social support co-occur with decreases in depressive symptoms and substance use problems among adults in permanent supportive housing: An 18-month longitudinal study. BMC Psychology, 9(1), 1-13.
- Tan, Z., de la Torre, J., Ma, W., Huh, D., Larimer, M. E., & Mun, E.-Y. (2022). A tutorial on
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