8 citations · 10 across the 7 of their papers we have counts for
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De-biased lasso for stratified Cox models with application to the national kidney transplant data
Lu Xia, Bin Nan, Yi Li
The Scientific Registry of Transplant Recipients (SRTR) system has become a rich resource for understanding the complex mechanisms of graft failure after kidney transplant, a cruci…
Inference for High Dimensional Censored Quantile Regression
Zhe Fei, Qi Zheng, Hyokyoung G. Hong +1
With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper stati…
Statistical Inference for Cox Proportional Hazards Models with a Diverging Number of Covariates
Lu Xia, Bin Nan, Yi Li
For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions on the inverse of the Fisher info…
A Revisit to De-biased Lasso for Generalized Linear Models
Lu Xia, Bin Nan, Yi Li
De-biased lasso has emerged as a popular tool to draw statistical inference for high-dimensional regression models. However, simulations indicate that for generalized linear models…
Estimation and Inference for High Dimensional Generalized Linear Models: A Splitting and Smoothing Approach
Zhe Fei, Yi Li
The focus of modern biomedical studies has gradually shifted to explanation and estimation of joint effects of high dimensional predictors on disease risks. Quantifying uncertainty…
Conditional Screening for Ultra-high Dimensional Covariates with Survival Outcomes
Hyokyoung Grace Hong, Jian Kang, Yi Li
Identifying important biomarkers that are predictive for cancer patients' prognosis is key in gaining better insights into the biological influences on the disease and has become a…