Zhiyong (Johnny) Zhang

Zhiyong (Johnny) Zhang

Professor

Ph.D., University of Virginia 

  • Quantitative

(574) 631-2902

zhiyongzhang@nd.edu

Office: 438 Corbett Family Hall
Lab: 430 Corbett Family Hall

Mailing Address:
390 Corbett Family Hall
Notre Dame, IN 46556

Lab for Big Data Methodology

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Our Lab for Big Data Methodology aims to develop better statistical methods and software in the areas of education, health, management and psychology. Our most recent research involves the development of new methods for social network and big data analysis. Particularly, we have contributed to the area of Bayesian methods, Network analysis, Big data analysis, Structural equation modeling, Longitudinal data analysis, Mediation analysis, and Statistical computing and programming.

Professor Zhang is open to mentoring graduate students in the fall

Profile

In general, Zhiyong Zhang is interested in developing and applying statistical methods in the areas of developmental and health research. Methodologically, his research interests include (1) continuous and categorical dynamic factor models, nonlinear time series models, and dynamical systems analysis, (2) linear and nonlinear models for analyzing longitudinal data, and (3) Bayesian methods and statistical computing. Substantively, he is interested in the analysis of intraindividual change and interindividual differences in change of life span development, cognitive aging, and emotion.

ND PIER Affiliate

Recent Publications

* denotes student author

  • *Kuang, Y., Zhang, Z., Duan, B., & Zhang, P. (accepted). Fuzzy Cognitive Maps-based Switched-Mode Power Supply Design Assistant System. IEEE Access.
  • *Che, C., Jin, I.-K., & Zhang, Z. (accepted). Network Mediation Analysis Using Model-based Eigenvalue Decomposition. Structural Equation Modelinghttps://doi.org/10.1080/10705511.2020.1721292
  • *Tong, X., & Zhang, Z. (2020). Robust Bayesian approaches in growth curve modeling: Using Student's t distributions versus semiparametric methods. Structural Equation Modeling, 27(4), 544-560https://doi.org/10.1080/10705511.2019.1683014
  • *Wen, Q., *Liu, H., & Zhang, Z. (2020). Generating multivariate non-normal random numbers with specified multivariate skewness and kurtosis. Behavior Research Methods, 52, 939–946. https://doi.org/10.3758/s13428-019-01291-5
  • *Wilcox, L.T., Jacobucci, R. & Zhang, Z. (2019). Bayesian Supervised Topic Modeling with Covariates (Abstract). Multivariate Behavioral Researchhttps://doi.org/10.1080/00273171.2019.1695568
  • *Du, H., Edwards, M., & Zhang, Z. (2019). Bayes factor in one-sample tests of means with a sensitivity analysis: A discussion of separate prior distributions. Behavior Research Methods51(5), 1998–2021. https://doi.org/10.3758/s13428-019-01262-w
  • Serang, S., Grimm, K. J., & Zhang, Z. (2019). On the correspondence between the latent growth curve and latent change score models. Structural Equation Modeling26(4), 623-635. https://doi.org/10.1080/10705511.2018.1533835  
  • *Cain, M. K., & Zhang, Z. (2019). Fit for a Bayesian: An evaluation of PPP and DIC for structural equation modeling. Structural Equation Modeling26(1), 39–50. https://doi.org/10.1080/10705511.2018.1490648
  • Yuan, K., Zhang, Z., & Deng, L. (2019). Fit indices for mean structures with growth curve models. Psychological Methods, 24(1), 36-53. https://doi.org/10.1037/met0000186