activity
20162022
most citedEstimation of time-varying reproduction numbers underlying epidemiological processes: a new statistical tool for the COVID-19 pandemic

110 citations · 129 across the 15 of their papers we have counts for

collaborators

15 papers

stat.ME2022

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…

stat.ME2022

Asynchronous and Error-prone Longitudinal Data Analysis via Functional Calibration

Xinyue Chang, Yehua Li, Yi Li

In many longitudinal settings, time-varying covariates may not be measured at the same time as responses and are often prone to measurement error. Naive last-observation-carried-fo…

stat.ME2021

De-biased Lasso for Generalized Linear Models with A Diverging Number of Covariates

Lu Xia, Bin Nan, Yi Li

Modeling and drawing inference on the joint associations between single nucleotide polymorphisms and a disease has sparked interest in genome-wide associations studies. In the moti…

stat.ME2021★ 1 cited

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…

stat.ME2021

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…

math.ST2020

Semiparametric regression of mean residual life with censoring and covariate dimension reduction

Ge Zhao, Yanyuan Ma, Huazhen Lin +1

We propose a new class of semiparametric regression models of mean residual life for censored outcome data. The models, which enable us to estimate the expected remaining survival…