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Dr. Jong-Hyeon Jeong

Mathematical Statistician, Biostatistics Branch

Biosketch:

Dr. Jeong joined the Biometric Research Program in the Division of Cancer Treatment and Diagnosis at the National Cancer Institute in 2023. Before joining the NCI, Dr. Jeong was a full professor at the Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh. His main statistical research areas have been time-to-event analysis and clinical trials, both explanatory and pragmatic. His recent research interests include causal inference, deep learning, empirical processes, mixed models, and prediction modeling using machine learning methods. Dr. Jeong is a fellow of the American Statistical Association (ASA), an elected member of the International Statistical Institute (ISI), and an elected member of Omicron of the Delta Omega Society (Honorary Public Health Society).

CV (Updated August, 2023)

Selected Publications:

Jeong, J. and Oakes, D. (2003). On the asymptotic relative efficiency of estimates from Cox's model. Sankhya, 65,411-421.

Jeong, J. and Fine, J. (2007). Parametric regression on cumulative incidence function. Biostatistics 8, 184-196.

Jeong, J., Jung, S, and Joseph Costantino. (2008). Nonparametric inference on median residual lifetimes in breast cancer patients. Biometrics 64, 157-163.

Zhou, M. and Jeong, J. (2011). Empirical likelihood ratio test for median and mean residual lifetime. Statistics in Medicine 30, 152-159.

Park, T., Jeong, J., and Lee, J. (2012). Nonparametric Bayesian inference on quantile residual life function. Statistics in Medicine 31, 1972-1985.

Ha, I., Christian, N., Jeong, J., Park, J., and Lee, Y. (2014). Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties. Statistical Methods in Medical Research, DOI: 10.1177/0962280214526193.

Balmert, L. and Jeong, J. (2016). Nonparametric inference on quantile lost lifespan. Biometrics, 73(1), 252-259.

Zhang, D. and Jeong, J. (2021). Inference on win ratio for cluster-randomized semi-competing risk data. Japanese Journal of Statistics and Data Science. In press.

Jia, Y. and Jeong, J. (2021). Deep learning for quantile regression: DeepQuantreg. Computational Statistics and Data Analysis. https://doi.org/10.1016/j.csda.2021.107323.

Pearce, T., Jeong, J., Jia, Y., and Zhu, J. (2022). Censored quantile regression neural networks. NeurIPS 2022.

Fisher, B, Jeong, J., Anderson, S. Bryant, J., Fisher, E., and Wolmark Norman. (2002). Twenty-five year findings from a randomized clinical trial comparing radical mastectomy with total mastectomy and with total mastectomy followed by radiation therapy. New England Journal of Medicine, vol. 347, 8, 567-575.

Swain SM, Jeong J., Geyer CE Jr., Costantino JP, Pajon ER, Fehrenbacher L, Atkins JN, Polikoff J, Vogel VG, Erban JK, Rastogi P, Livingston RB, Perez EA, Mamounas EP, Land SR, Ganz PA, and Wolmark N. (2010). Longer duration of treatment and chemotherapy-induced amenorrhea are associated with improved survival in early breast cancer. New England Journal of Medicine 362, 2053-65.

Romond, E., Jeong, J., Rastogi, P. et al. (2012). Seven-year follow-up assessment of cardiac function in NSABP B-31, a randomized trial comparing doxorubicin and cyclophosphamide Followed by paclitaxel (ACP) with ACP plus trastuzumab as adjuvant therapy for patients with node-positive, Human Epidermal Growth Factor Receptor 2-positive breast cancer. Journal of Clinical Oncology 30, 3792-3799.

Pogue-Geile, K.L., Kim, C., Jeong, J. et al. (2013). Predicting degree of benefit from adjuvant trastuzumab in NSABP Trial B-31. Journal of the National Cancer Institute, 105, 1782-1788.

Mamounas EP, Bandos H, Rastogi P, Lembersky BC, Jeong J, Geyer CE Jr. et al. (2022). Ten-year results from NRG Oncology/NSABP B-42: Extended Letrozole Therapy in Postmenopausal Women with Hormone-receptor Positive, Early-stage Breast Cancer. Journal of National Cancer Institute. DOI: 10.1093/jnci/djad078.