Recent publications
Statistical Methods
Wang, D., Ye, W. and He, K.*
Kullback-Leibler-based discrete relative risk models for integration of published prediction models with new dataset
Proceedings of Machine Learning Research
2021 : in press
Statistical Methods
He, K.*, Kang, J., Zhu, J. and Li, Y.
Stratified Cox models with time-varying effects for national kidney transplant patients: a new block-wise steepest ascent method
Biometrics
2021: in press
Machine Learning
Guo, Z., Xiao, D. and He, K.*
Early warning of some notifiable infectious diseases in China by the artificial neural network
Royal Society Open Science
2020: 7(2), 191420
Healthcare Provider Profiling
Xia, L., He, K., Li, Y.M. and Kalbfleisch, J.D.
Accounting for total variationand robustness in profiling health care providers
Biostatistics
2020: 26(3), 635-645.
Healthcare Provider Profiling
He, K., Dahlerus, C., Xia, L., Li, Y.M. and Kalbfleisch, J.D.
The profiling inter-unit reliability.
Biometrics
2020: 76(2), 654-663.
Healthcare Provider Profiling
Wang, L., He, K. and Schaubel, D.E.
Penalized survival models for the analysis of alternating recurrent event data
Biometrics
2020: 76(2), 448-459.
Statistical Methods
He, K., Li, Y., Rao, P.S., Sung, R.S. and Schaubel, D.E.
Prognostic score matching methods for estimating the average treatment effect on the survival function when treatment is time-dependent.
Lifetime Data Analysis
2020: 26(3), 451-470.
Statistical Methods
He, K.*, Wang, Y., Zhou, X., Xu, H. and Huang, C.
An improved variable selection procedure for adaptive Lasso in high-dimensional survival analysis.
Lifetime Data Analysis
2019: 25(3), 569-585.
Healthcare Provider Profiling
He, K., Ashby, V.B. and Schaubel, D.E.
Evaluating center-specific long term outcomes through differences in mean survival time
Statistics in Medicine
2010: 38(11), 1957-1967.
Healthcare Provider Profiling
He, K., Kalbfleisch, J.D., Yang, Y. and Fei, Z.
Inter-unit reliability for nonlinear models
Royal Society Open Science
2019: 38(5), 844-854.
Big Data
He, K., Kang, J., Hong, H.G., Zhu, J., Li, Y.M., Lin, H.Z., Xu, H. and Li, Y.
Covariance-insured screening
Computational Statistics & Data
2019: 132, 110-114.
Review
He, K., Xu, H. and Kang, J.
A selective overview of feature screening methods with applications to neuroimaging data.
WIRES Computational Statistics
2019: 11(2), e1454.
Healthcare Provider Profiling
He, K.*, Kang, J., Zhu, J. and Li, Y.
Inter-unit reliability for quality measure testing
Journal of Hospital Administration
2019: 8(2), 1-6
Statistical Methods
He, K., Zhou, X., Jiang, H., Wen, X.Q. and Li, Y.
Indirect and direct standardization for evaluating transplant centers
Statistical Applications in Genetics and Molecular Biology
2018: 17(6)
Book Chapter
He, K., Li, Y.M., Wei, Q.Y. and Li, Y.
Computationally efficient approach for modeling complex and big survival data
Big and Complex Data Analysis: Statistical Methodologies and Applications
2017: 193-207.
Statistical Methods
He, K., Yang, Y., Li, Y.M., Zhu, J. and Li, Y.
Modeling time-varying effects with large-scale survival data: an efficient quasi-Newton approach
Journal of Computational and Graphical Statistics
2017: 26(3), 635-645.
Survival Analysis
Wang, L., He, K. and Schaubel, D.E.
Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates
Bioinformatics
2016: 32(1), 50-57.
Healthcare Provider Profiling
He, K.* and Schaubel, D.E.
Standardized mortality ratio for evaluating center-specific mortality: assessment and alternative
Statistics in Biosciences
2015: 7, 296-321.
Healthcare Provider Profiling
He, K.* and Schaubel, D.E.
Semiparametric methods for relative risk center effect measures
Lifetime Data Analysis
2014: 20(4), 619-644.
Healthcare Provider Profiling
He, K.* and Schaubel, D.E.
Methods for estimating center effects in survival analysis using direct standardization
Statistics in Medicine
2014: 33(12), 2048-2061.
