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Sang Kyu Lee
Postdoctoral Fellow
National Cancer Institute
sangkyu.lee (at) nih.gov
Publications
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* denotes equal contribution
† denotes corresponding author
underline
denotes students whom I advised/co-advised
Preprints/Submitted Papers
StaRQR-K: Discovering Regulatory Switches in Cancer Epigenomes via False Discovery Rate Controlled Regional Quantile Regression
Lee, S. K.
, Zhang, T., Hong, H. G.
†
, and Weng, H.
†
submitted (2025+)
High-dimensional Partial Linear Model with Trend Filtering
Lee, S. K.
, Loftfield, E., Hong, H. G.
†
, and Weng, H.
†
arXiv (2024+)
Causal Decomposition Framework for Quantifying Intervenable Cancer Health Disparities
Xia, F.*,
Lee, S. K.*
, Kim, S., Blum, K., Hong, H. G., Canchola, A. J., Shariff-Marco, S., Gomez, S. L. and Kim, M.-O.
†
submitted (2025+)
Decomposition of Longitudinal Disparities: an Application to the Fetal Growth-Singletons Study
Lee, S. K.
, Kim, S., Kim, M.-O., Grantz, K. L., and Hong, H. G.
†
arXiv (2024+)
Winner of the ASA Statistics in Epidemiology Section Junior Researcher/Student Paper Competition in Joint Statistical Meeting (JSM) 2024
Published Papers (Statistical Methods, Theories, and Software)
A Comprehensive Estimator for the Fréchet Distribution: Asymptotical Efficiency, and Practical Applications
Lee, S. K.
, Hong, H. G., and Kim, H.-M.
†
Journal of Korean Statistical Society (2025)
MLEce: Statistical Inference for Asymptotically Efficient Closed-form Estimators in R
Zhao, J., Kim, Y.-K., Jang, Y.-H., Chang, J. H.,
Lee, S. K.
, and Kim, H.-M.
†
SoftwareX (2024)
An Asymptotically Efficient Closed-form Estimator for the Dirichlet Distribution
Chang, J. H.,
Lee, S. K.
, and Kim, H.-M.
†
Stat (2023)
Quantile Forward Regression for High-dimensional Survival Data
Lee, E. R., Park, S.,
Lee, S. K.
, and Hong, H. G.
†
Lifetime Data Analysis (2023)
Two Tests Using More Assumptions but Lower Power
Lee, S. K.
, and Kim, H.-M.
†
Communications for Statistical Applications and Methods (2023)
Further Sharpening of Jensen's Inequality
Lee, S. K.
, Chang, J. H., and Kim, H.-M.
†
Statistics (2021)
Honorable Mention from Student Paper Competition for Korean Statistical Society Academic Conference 2019
EMSS: New EM-type Algorithms for the Heckman Selection Model in R
Yang, K.
,
Lee, S. K.
, Zhao, J., and Kim, H.-M.
†
R Journal (2021)
Some Counterexamples of a Skew-normal Distribution
Zhao, J.,
Lee, S. K.
, and Kim, H.-M.
†
Communications for Statistical Applications and Methods (2019)
Published Papers (Collaborative Applications)
Identification and Validation of Poly-Metabolite Scores for Diets High in Ultra-Processed Food: An Observational Study and Post-Hoc Randomized Controlled Crossover-Feeding Trial
Abar, L., Steele, E. M.,
Lee, S. K.
, Kahle, L., Moore, S. C., Watts, E., Matthews, C., Herrick, K., Hall, K. D., O’Connor, L. E., Freedman, N. D., Sinha, R., Hong, H. G., and Loftfield, E.
†
PLOS Medicine (2025)
Superficial X-ray in the treatment of nonaggressive basal and squamous cell carcinoma in the elderly: A 22-year retrospective analysis
Mattia, A., Thompson, A.,
Lee, S. K.
, Hong, H. G., Green, W. H.
†
, and Cognetta Jr, A. B.
Journal of the American Academy of Dermatology (2024)
Statistical Software
RQRscreen
Maintainer
An R function for a regional quantile regression model to screening features with ultrahigh-dimensional data
GitHub
frechetAEE
Maintainer
An R package for an asymptotically efficient estimator for the Frechet distribution
GitHub
plmR
Maintainer
An R package for estimating and fitting various high-dimensional partial linear models
GitHub
vcPB
Maintainer
An R package for estimating the disparity between a majority group and a minority group based on the extended model of the Peters-Belson method
CRAN
GitHub
MLEce
Author
An R package for estimating asymptotically efficient closed-form estimators and providing the goodness of fit, estimates, plots and etc
CRAN
EMSS
Maintainer
An R package for fitting some new EM-Type estimation methods for the Heckman selection model
CRAN
GitHub
DiSSMod
Maintainer
An R package for fitting sample selection models for discrete response variables
CRAN
Shiny