Han Du

Associate Professor
Ph.D.: University of Notre Dame
Primary Area: Quantitative
Address: Pritzker Hall 4538
Email: hdu@psych.ucla.edu
Lab Website: https://dulab.psych.ucla.edu

Research and Teaching Interests:

My methodological interests have evolved along four inter-related lines: (1) Bayesian methods and statistical computing; (2) longitudinal data analysis and time series analysis; (3) structural equation modeling; and (4) study design and sample size determination. I also work on developing new meta-analysis and machine learning techniques. From a substantive perspective, I am interested in applying quantitative methods in developmental, clinical, cognitive, educational, and health research.

I am currently accepting applications from prospective graduate students.

Representative Publications:

Please refer to my CV for the full list of publications.

* indicates student authors and postdoctoral researchers

Du, H., & Wu, H. (2024). Estimating the Weight Matrix in Distributionally Weighted Least Squares Estimation: An Empirical Bayesian Solution. Structural Equation Modeling: A Multidisciplinary Journal, 31(6), 952-964.

Du, H., Keller, B. T., *Alacam, E., & Enders, C. K. (2023). Comparing DIC and WAIC for multilevel models with missing data. Behavior Research Methods. Advance online publication.

*Alacam, E., Enders, C. K., Du, H., & Keller, B. T. (2023). A factored regression model for composite scores with item-level missing data. Psychological Methods. Advance online publication.

Du, H. (2023) Extended unbiased distribution free estimator with mean structures. Structural Equation Modeling: A Multidisciplinary Journal. Advance online publication.

Du, H., Ke, Z., Jiang, G., & Huang, S. (2022). The Performances of Gelman-Rubin and Geweke’s Convergence Diagnostics of Monte Carlo Markov Chains in Bayesian Analysis. Journal of Behavioral Data Science, 2(2), 47-72.

Du, H. & Bentler, P.M. (2022). 40-Year Old Unbiased Distribution Free Estimator Reliably Improves SEM Statistics for Nonnormal Data. Structural Equation Modeling: A Multidisciplinary Journal, 29(6), 872-887

Du, H., *Alacam, E., *Mena, S., & Keller, B. T. (2022). Compatibility in imputation specification. Behavior Research Methods, 1-19. Advance online publication

Du, H., Jiang, G., & Ke, Z. (2022). Bootstrap-based between-study heterogeneity tests in meta-analysis. Multivariate Behavioral Research, 1–20. Advance online publication.

Du, H., Bentler, P.M., & Rosseel, Y. (2022). Distributionally-weighted least squares in growth curve modeling. Structural Equation Modeling, 29(1), 1-22.

Du, H., & Enders, C. K., Keller, B. T., Bradbury, T. N., & Karney, B. R. (2022). A Bayesian latent variable selection model for nonignorable missingness. Multivariate Behavioral Research, 57(2-3), 478-512.

Reise, S.P., Du, H., *Wong, E., *Hubbard, A., & Haviland, M. (2021). The Log Logistic item response theory model and the measurement of non-cognitive constructs. Psychometrika, 86(3), 800–824.

Du, H., & Bentler, P. M. (2021). Distributionally weighted least squares in structural equation modeling. Psychological Methods, 1-22. Advance online publication.

Du, H., Bradbury, T.N., Lavner, J.A., Meltzer, A.L., McNulty, J.K., Neff, L.A., & Karney, B.R. (2020). A comparison of Bayesian synthesis approaches for comparing two group means. Research Synthesis Methods, 11, 36-65.

Du, H., & Wang, L. (2020). Testing variance components in linear mixed modeling using permutation. Multivariate Behavioral Research, 55(1), 120-136.

Du, H., Liu, F., & Wang, L. (2017). A Bayesian” fill-in” method for correcting for publication bias in meta-analysis. Psychological Methods, 22(4), 799-817.