My methodological interests have evolved along three inter-related lines: (1) Bayesian methods and statistical computing; (2) longitudinal data analysis and time series analysis; and (3) study design and sample size determination. From a substantive perspective, I am interested in applying quantitative methods in developmental, clinical, cognitive, educational, and health research. Specifically, I focus on developing and applying appropriate Bayesian, longitudinal, and time series models and developing applicable statistical methods for analyzing various complex data and facilitating study design.
Enders, C.K., Du, H., & Keller, B.T. (in press). Substantive model-compatible imputation for multilevel regression models with random coefficients, interaction effects, and other non-linear terms. Psychological Methods.
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 studies comparing two means: A tutorial. Research synthesis methods, 11(1), 36-65.
Ray, L. A., Du, H., Grodin, E., Bujarski, S., Meredith, L., Ho, D., ... & Wassum, K. (2020). Capturing habitualness of drinking and smoking behavior in humans. Drug and Alcohol Dependence, 207, 107738.
Du, H., & Wang, L. (2019). Testing variance components in linear mixed modeling using permutation. Multivariate behavioral research, 1-17.
Du, H., Edwards, M. C., & Zhang, Z. (2019). Bayes factor in one-sample tests of means with a sensitivity analysis: A discussion of separate prior distributions. Behavior research methods, 51(5), 1998-2021.
Park, I. J., Du, H., Wang, L., Williams, D. R., & Alegría, M. (2019). The Role of Parents’ Ethnic-Racial Socialization Practices in the Discrimination–Depression Link among Mexican-Origin Adolescents. Journal of Clinical Child & Adolescent Psychology, 1-14.
Gao, M., Du, H., Davies, P. T., & Cummings, E. M. (2019). Marital conflict behaviors and parenting: Dyadic links over time. Family relations, 68(1), 135-149.
Enders, C. K., Hayes, T., & Du, H. (2018). A comparison of multilevel imputation schemes for random coefficient models: Fully conditional specification and joint model imputation with random covariance matrices. Multivariate behavioral research, 53(5), 695-713.
Du, H., & Wang, L. (2018). Investigating reliabilities of intraindividualvariability indicators with autocorrelated longitudinal data. Multivariate Behavioral Research, 53(4), 502-520.
Park, I. J. K., Du, H., Wang, L., Williams, D. R., & Alegría, M. (2018). Racial/ethnic discrimination and mental health in Mexican-origin youths and their parents: Testing the “linked lives” hypothesis. Journal of Adolescent Health, 62, 480-487.
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.
Planalp, E.M., Du, H., Braungart-Rieker, J.M., & Wang, L. (2017). Growth curve modeling to studying change: A comparison of approaches using longitudinal dyadic data with distinguishable dyads. Structural Equation Modeling, 24(1), 129-147.
Du, H., Zhang, Z., & Yuan, K.-H. (2016). Power analysis for t-test with non-normal data and unequal variancess. In van der Ark, L.A., Culpepper, S., Douglas, J.A., Wang, W.-C., & Wiberg, M. (Eds.), Proceedings of Quantitative Psychology: The 81st Annual Meeting of the psychometric Society. New York, NY: Springer.
Du, H., & Wang, L. (2016). A Bayesian power analysis procedure considering uncertainty in effect size estimates from a meta-analysis. Multivariate Behavioral Research, 51(1), 589-605.
Du, H., & Wang, L. (2016). The impact of the number of dyads on estimation of dyadic data analysis using multilevel modeling. Methodology, 12(1), 21-31.