Factor Analysis and Missing Data

Kim, D.S. & Zhou Q. (2026). Identification of Nonlinear and Dependent Latent Factor Structure through Clique Search. Preprint. arXiv:2609.32926. [Link]

Kim, D.S. (2026). A Stochastic EM Algorithm with Sampling-Importance Resampling for Missing Data in Regression with Nonlinear Predictors. Preprint. arXiv:2609.23747. [Link]

Kim, D.S. (2026). A Hybrid EM Algorithm for Linear Two-Way Interactions with Missing Data. Journal of Educational and Behavioral Statistics. 51(1), 38–59. [Link]

Kim, D.S., Lu, A., & Zhou, Q. (2025). The Correlation Thresholding Algorithm for Exploratory Factor Analysis. Structural Equation Modeling: A Multidisciplinary Journal. 32(6), 966–979. [Link]

Kim, D. S., & Zhou, Q. (2023). Structure Learning of Latent Factors via Clique Search on Correlation Thresholded Graphs. Proceedings of the 40th International Conference on Machine Learning. 202, 16978–16996. [Link]

Kim, D. S., Reise, S. P., & Bentler, P. M. (2018). Identifying Aberrant Data in Structural Equation Models with IRLS-ADF. Structural Equation Modeling: A Multidisciplinary Journal, 25(3), 343–358. [Link]

Reise, S. P., Kim, D. S., Mansolf, M., & Widaman, K. F. (2016). Is the Bifactor Model a Better Model or Is It Just Better at Modeling Implausible Responses? Application of Iteratively Reweighted Least Squares to the Rosenberg Self-Esteem Scale. Multivariate Behavioral Research, 51(6), 818–838. [Link]

Statistical Inference for the Behavioral Sciences

Kim, D. S., & McCabe, C. J. (2022). The Partial Derivative Framework for Substantive Regression Effects. Psychological Methods, 27(1), 121–141. [Link]

McCabe, C. J., Halvorson, M. A., King, K. M., Cao, X., & Kim, D. S. (2022). Interpreting Interaction Effects in Generalized Linear Models of Nonlinear Probabilities and Counts. Multivariate Behavioral Research, 57(2–3), 243–263. [Link]

Halvorson, M. A., McCabe, C. J., Kim, D. S., Cao, X., & King, K. M. (2022). Making Sense of Some Odd Ratios: A Tutorial and Improvements to Present Practices in Reporting and Visualizing Quantities of Interest for Binary and Count Outcome Models. Psychology of Addictive Behaviors, 36(3), 284–295. [Link]

McCabe, C. J., Kim, D. S., & King, K. M. (2018). Improving Present Practices in the Visual Display of Interactions. Advances in Methods and Practices in Psychological Science, 1(2), 147–165. [Link]

Applied Measurement

King, K. M., Kim, D. S., & McCabe, C. J. (2018). Random Responses Inflate Statistical Estimates in Heavily Skewed Addictions Data. Drug and Alcohol Dependence, 183, 102–110. [Link]

Kim, D. S., McCabe, C. J., Yamasaki, B. L., Louie, K. A., & King, K. M. (2018). Detecting Careless Responders with Infrequency Scales Using an Error Balancing Threshold. Behavior Research Methods, 50(5), 1960–1970. [Link]