Ai Ye

• BS, Engineering, 2012, Wuhan University, Hubei, China
• MA, Social Research Methodology, 2014, University of California, Los Angeles, USA
• MS, Statistics, 2020, University of North Carolina, Chapel Hill, USA
• PhD, Quantitative Psychology, 2022, University of North Carolina, Chapel Hill, USA

Research interests

• Advanced psychometric modeling
• Longitudinal Structural Equation Modeling
• Dynamic modeling
• Machine learning methods

Selected publications

Ye, A., & Bollen, K. A. (2024). Path and direction discovery in individual dynamic factor models: A regularized hybrid unified Structural Equation Modeling with latent variable. Multivariate Behavioral Research, 59(5), 1019–1042. https://doi.org/10.1080/00273171.2024.2354232

Ye, A., & Bollen, K. A. (2022). Can we distinguish between different longitudinal models for estimating nonlinear trajectories? Structural Equation Modeling: A Multidisciplinary Journal, 29(1), 57–69. https://doi.org/10.1080/10705511.2021.1959333

Ye, A., Gates, K. M., Henry, T. R., & Luo, L. (2021). Path and directionality discovery in individual dynamic models: A regularized unified Structural Equation Modeling approach for hybrid vector autoregression. Psychometrika, 86(2), 404–441. https://doi.org/10.1007/s11336-021-09753-6

Ye, A., Resnick, I., Hansen, N., Rodrigues, J., Rinne, L., & Jordan, N. C. (2016). Pathways to fraction learning: Numerical abilities mediate the relation between early cognitive competencies and later fraction knowledge. Journal of Experimental Child Psychology, 152, 242–263. https://doi.org/10.1016/j.jecp.2016.08.001