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Han Du
Assistant Professor
University of Notre Dame
Primary Area:
Life Sciences Building 5805
Research and Teaching Interests:

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.

Representative Publications:

Du, H., & Wang, L. (accepted). Testing variance components in linear mixed modeling using permutation. Multivariate Behavioral Research.

Du, H., Bradbury, T.N., Lavner, J.A., Meltzer, A.L., McNulty, J.K., Neff, L.A., & Karney, B.R. (accepted). A Comparison of Bayesian Synthesis Approaches for Comparing Two Group Means. Research Synthesis Methods.

Du, H., Edwards, M.C., & Zhang, Z. (accepted). Bayes factor in one sample tests of means with a sensitivity analysis: A discussion of separate prior distributions. Behavior Research Methods.

Enders, C.K., Du, H., & Keller, B.T. (accepted). Substantive model-compatible imputation for multilevel regression models with random coefficients, interaction effects, and other non-linear terms. Psychological Methods.

Park, I. J. K., Du, H., Wang, L., Williams, D. R., & Alegría, M. (in press). The role of parents’ ethnic-racial socialization practices in the discrimination—depression link among Mexican-origin adolescents. Journal of Clinical Child and Adolescent Psychology.

Enders, C.K., Hayes, T., & Du, H. (in press). A comparison of multilevel imputation schemes for random coefficient models: Fully conditional specification and joint model imputation with random covariance matrices. Multivariate Behavioral Research.

Gao, M. M., Du, H., Davies, P. T., & Cummings, E. Mark. (in press). Marital conflict behaviors and parenting: Dyadic links over time. Family Relations.

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.