Publications

✱co-first author

  1. Corliss B, Wang Y, Driscoll F, Shakeri H, and Bourne PE (2024). MAD-FC: A Fold Change Visualization with Readability, Proportionality, and Symmetry. PLOS One, accepted.
  2. Li S, Wang Y✱, Peng L, Tudorascu DL, Yan G, He J, and Zhang T (2023). Whole-Brain Directed Network Analysis of fMRI Data. Statistics and Its Interface, accepted.
  3. Wang Y, Yan G, Wang X, Li S, Peng L, Tudorascu DL, and Zhang T (2022). A Variational Bayesian Approach to Identifying Whole-Brain Directed Networks with fMRI Data. The Annals of Applied Statistics, 17(1): 518-538.
  4. Wang Y, Yan G, Tanabe S, Liu C-C, Moosa S, Quigg M, and Zhang T (2022). High-Dimensional Directional Brain Network Analysis for Focal Epileptic Seizures. arXiv:2208.07991.
  5. Corliss B, Wang Y, Shakeri H, and Bourne, PE (2022). The Least Difference in Means: A Statistic for Effect Size Strength and Practical Significance. arXiv:2205.12958.
  6. Li H, Wang Y✱, Yan G, Sun Y, Tanabe S, Liu C-C, Quigg M, and Zhang T (2021). A Bayesian State-Space Approach to Mapping Directional Brain Networks. Journal of the American Statistical Association, 116(536): 1637-1647.
  7. Li H, Wang Y✱, Tanabe S, Sun Y, Yan G, Quigg M, and Zhang T (2021). Mapping Epileptic Directional Brain Networks Using Intracranial EEG Data. Biostatistics, 22(3): 613-628.
  8. Zhang T, Pham M, Yan G, Wang Y, Medina-Devilliers S, and Coan JA (2021). Spatial-Temporal Analysis of Multi-Subject Functional Magnetic Resonance Imaging Data. Econometrics and Statistics, https://doi.org/10.1016/j.ecosta.2021.02.006.
  9. Zhang T, Sun Y, Li H, Yan G, Tanabe S, Miao R, Wang Y, Caffo B, and Quigg M (2020). Bayesian Inference of a Directional Brain Network for Intracranial EEG Data. Computational Statistics and Data Analysis, 144: 106847.

Under review/In preparation

  1. Wang Y, Li S✱, He J, Peng L, Tudorascu DL, Schaeffer DJ, Schaeffer L, Szczupak D, Park JE, Rizzo SJS, Carte GW, Silva AC, Zhang T, and the Alzheimer’s Disease Neuroimaging Initiative (2024). Analysis of Functional Connectivity Changes from Childhood to Old Age: A Study Using HCP-D, HCP-YA, and HCP-A Datasets. Under review.
  2. Wang Y, Guo Y (2024). An Empirical-Topology-Informed Bayesian Blind Source Separation for Investigating Whole-Brain Functional Connectivity. Manuscript.
  3. Corliss B, Wang Y, Shakeri H, and Bourne, PE (2022). Contra-Analysis: Prioritizing Meaningful Effect Size in Scientific Research. Under review.