Higher criticism for rare and weak non-proportional hazard deviations in survival analysis

A Kipnisand others

Testing for latent structure via the Wilcoxon--Wigner random matrix of normalized rank statistics

Joshua Cape, Jonquil Z Liao

Summary This paper considers the problem of testing for latent structure in large symmetric data matrices. The goal here is to devel...

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates

Wensheng Guo, Tianhao Wang

Variable Significance Testing for the Deep Cox Model

Qixian Zhong, Jonas Mueller, Jane-Ling Wang

Likelihood Methods in Survival Analysis: With R Examples

Lu Mao

SurvSTAAR: A powerful statistical framework for rare variant analysis of time-to-event traits in large-scale whole-genome sequencing studies

Yidan Cui, Shiyang Ma, Yuxin Yuan et al.

Understanding Inequalities in Cancer Survival Using Bayesian Machine Learning

Antonio R. Linero, Piyali Basak, Camille Maringe et al.

Efficient and Robust Transfer Learning of Optimal Individualized Treatment Regimes with Right-Censored Survival Data

Pan Zhao, Shu Yang, Julie Josse

An individualized treatment regime (ITR) is a decision rule that assigns treatments based on patients' characteristics. The value function of an ITR i...

Efficient nonparametric estimators of discrimination measures with censored survival data

Torben Martinussen, Marie Skov Breum

Checking the Cox Proportional Hazards Model with Interval-Censored Data

Yangjianchen Xu, Donglin Zeng, D. Y. Lin

Communication-Efficient Distributed Estimation and Inference for Cox’s Model

Jianqing Fan, Pierre Bayle, Zhipeng Lou

Multicalibration for Modeling Censored Survival Data with Universal Adaptability

Hanxuan Ye, Hongzhe Li

Abstract

Modelling tree survival for investigating climate change effects

Nicole Augustin, Axel Albrecht, Karim Anaya-Izquierdo et al.

Multicalibration for Modeling Censored Survival Data with Universal AdaptabilityGet access

Hanxuan YeandHongzhe Li

Kernel Meets Sieve: Transformed Hazards Models with Sparse Longitudinal Covariates

Dayu Sun, Zhuowei Sun, Xingqiu Zhao et al.