Efficient estimation of the maximal association between multiple predictors and a survival outcome
From MaRDI portal
Publication:6183767
DOI10.1214/23-aos2313arXiv2112.10996OpenAlexW4389818603MaRDI QIDQ6183767
Ian W. McKeague, Tzu-Jung Huang, Alex Luedtke
Publication date: 4 January 2024
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2112.10996
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Testing in survival analysis and censored data (62N03)
Cites Work
- Measuring and testing dependence by correlation of distances
- Regularization for Cox's proportional hazards model with NP-dimensionality
- Cox's regression model for counting processes: A large sample study
- Variable selection in the accelerated failure time model via the bridge method
- Estimation in a linear regression model with censored data
- Principled sure independence screening for Cox models with ultra-high-dimensional covariates
- Contributions to a general asymptotic statistical theory. With the assistance of W. Wefelmeyer
- Regression analysis with randomly right-censored data
- Estimation in semiparametric models. Some recent developments
- Conditional screening for ultra-high dimensional covariates with survival outcomes
- Unified methods for censored longitudinal data and causality
- Exponential inequalities for martingales, with application to maximum likelihood estimation for counting processes
- Quantile-adaptive model-free variable screening for high-dimensional heterogeneous data
- Comment on: ``Models as (deliberate) approximations
- A significance test for the lasso
- Covariate selection for semiparametric hazard function regression models
- Survival Analysis with High-Dimensional Covariates: An Application in Microarray Studies
- Variable selection in partly linear regression model with diverging dimensions for right censored data
- Censored rank independence screening for high-dimensional survival data
- Tests for Coefficients in High-dimensional Additive Hazard Models
- The Dantzig Selector in Cox's Proportional Hazards Model
- Integrated powered density: Screening ultrahigh dimensional covariates with survival outcomes
- Elastic net for Cox’s proportional hazards model with a solution path algorithm
- Regularized Estimation in the Accelerated Failure Time Model with High-Dimensional Covariates
- Score test variable screening
- Variable Selection in Semiparametric Linear Regression with Censored Data
- Penalized Estimating Functions and Variable Selection in Semiparametric Regression Models
- Regularized Estimation for the Accelerated Failure Time Model
- Implicit Alternatives and the Local Power of Test Statistics
- Linear regression with censored data
- Robust estimation and outlier detection with correlation coefficients
- On central limit theorems for martingale triangular arrays
- Locally efficient estimation of the survival distribution with right-censored data and covariates when collection of data is delayed
- Rank-based inference for the accelerated failure time model
- Testing and Confidence Intervals for High Dimensional Proportional Hazards Models
- Post‐selection inference for ‐penalized likelihood models
- Parametric-Rate Inference for One-Sided Differentiable Parameters
- Confidence intervals for high-dimensional Cox models
- Copula-based Partial Correlation Screening: a Joint and Robust Approach
- Independent Screening for Single-Index Hazard rate Models with Ultrahigh Dimensional Features
- The Lq-norm learning for ultrahigh-dimensional survival data: an integrative framework
- Conditional quantile correlation learning for ultrahigh dimensional varying coefficient models and its application in survival analysis
- Inference for Low-Dimensional Covariates in a High-Dimensional Accelerated Failure Time Model
- A Generic Sure Independence Screening Procedure
- Marginal screening for high-dimensional predictors of survival outcomes
- Survival impact index and ultrahigh‐dimensional model‐free screening with survival outcomes
- An overview of techniques for linking high‐dimensional molecular data to time‐to‐event endpoints by risk prediction models
- The dantzig selector for censored linear regression models
- Adaptive Lasso for Cox's proportional hazards model
