Timothy Hayes
Affiliations: | 2013- | Psychology | University of Southern California, Los Angeles, CA, United States |
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Publications
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| Hayes T. (2021) R-squared change in structural equation models with latent variables and missing data. Behavior Research Methods |
| Hayes T, Usami S. (2020) Factor Score Regression in the Presence of Correlated Unique Factors. Educational and Psychological Measurement. 80: 5-40 |
| Usami S, Jacobucci R, Hayes T. (2018) The performance of latent growth curve model-based structural equation model trees to uncover population heterogeneity in growth trajectories Computational Statistics. 34: 1-22 |
| Hayes T, McArdle JJ. (2017) Evaluating the Performance of CART-Based Missing Data Methods Under a Missing Not at Random Mechanism. Multivariate Behavioral Research. 1-2 |
| Usami S, Hayes T, McArdle J. (2017) Fitting Structural Equation Model Trees and Latent Growth Curve Mixture Models in Longitudinal Designs: The Influence of Model Misspecification Structural Equation Modeling: a Multidisciplinary Journal. 24: 585-598 |
| Hayes TK, Neel NF, Hu C, et al. (2015) Long-term ERK Inhibition in KRAS-Mutant Pancreatic Cancer Is Associated with MYC Degradation and Senescence-like Growth Suppression. Cancer Cell |
| Usami S, Hayes T, McArdle JJ. (2015) On the Mathematical Relationship Between Latent Change Score and Autoregressive Cross-Lagged Factor Approaches: Cautions for Inferring Causal Relationship Between Variables. Multivariate Behavioral Research. 50: 676-87 |
| Hayes T, Usami S, Jacobucci R, et al. (2015) Using Classification and Regression Trees (CART) and Random Forests to Analyze Attrition: Results From Two Simulations. Psychology and Aging |
| Usami S, Hayes T, McArdle JJ. (2015) Inferring Longitudinal Relationships Between Variables: Model Selection Between the Latent Change Score and Autoregressive Cross-Lagged Factor Models Structural Equation Modeling |