Faculty

Chaeryon Kang, PhD

Chaeryon Kang, PhD

Visiting Associate Professor of Psychiatry

Contact Details

3811 O'Hara St.
Pittsburgh
 
PA
 
15213
Email
Website
Kang Research Website

Education & Training

PhD
Biostatistics, University of North Carolina at Chapel Hill, Gillings School of Global Public Health
Vaccines and Infectious Diseases/Public Health Sciences, Fred Hutchinson Cancer Research Center

Professional Affiliations

Member, American Statistical Association
Member, The International Biometric Society, Eastern North American Region (ENAR)
Member, Korean International Statistical Society

Research Interests

Biostatistics
Selected Research Publications & Products
  1. Gorczyca MT and Kang C. On quantifying heterogeneous treatment effects with regression-based individualized treatment rules: Loss function families and bounds on estimation error (2024). Stat, 13(2): e680. doi:https://10.1002/sta4.680
  2. Kang C and Huang Y. Identification of immune response combinations associated with heterogeneous infection risk in the immune correlate analysis of HIV vaccine studies (2023). Annals of Applied Statistics, 17(2): 1199-1219. doi:https://10.1214/22-AOAS1665
  3. Kang C, Zhang D, Schuster J, Kogan J, Nikolajski C, and Reynolds III CF. Bias-corrected and doubly robust inference for the three-level longitudinal cluster-randomized trials with missing continuous outcomes and small number of clusters:simulation study and application to a study for adults with serious mental illnesses. Con-temporary Clinical Trials Communications: study design & statistical methods (2023). Vol.35, October 2023, p.101194. doi:10.1016/j.conctc.2023.101194.
  4. Kang C , Janes H, and Huang, Y. Combining biomarkers to optimize patient treatment recommendation (2014). Biometrics, 70(3): 695-707. doi:https://doi.org/10.1111/biom.1219 (with discussion)
  5. Kang C, Janes H, Tajik P, Groen H, Mol BWJ, Koopmans CM, Broekhuijsen K, Zwertbroek E, van Pampus MG, and Franssen MTM. Evaluation of biomarkers for treatment selection using individual participant data from multiple clinical trials (2018). Statistics in Medicine, 37(9):1439-1453. doi:https://doi.org/10.1002/sim.7608