Proportional hazards models with continuous marks

DOI10.1214/07-AOS554zbMath1155.62075arXiv0903.0487OpenAlexW2012866524WikidataQ42041320 ScholiaQ42041320MaRDI QIDQ1002166

Peter B. Gilbert, Ian W. McKeague, Yanqing Sun

Publication date: 25 February 2009

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/0903.0487

zbMATH Keywords

semiparametric modelcompeting risksfailure time datadistribution-free confidence bandsgenetic dataHIV vaccine trialpointwise and simultaneous confidence bands

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Central limit and other weak theorems (60F05) Censored data models (62N01) Estimation in survival analysis and censored data (62N02) Testing in survival analysis and censored data (62N03)

Related Items (8)

Mark-specific additive hazards regression with continuous marks ⋮ Incorporating founder virus information in vaccine field trials ⋮ Estimation of Stratified Mark-Specific Proportional Hazards Models with Missing Marks ⋮ Goodness-of-fit test of the stratified mark-specific proportional hazards model with continuous mark ⋮ A joint modeling approach for analyzing marker data in the presence of a terminal event ⋮ Mark‐Specific Hazard Ratio Model with Multivariate Continuous Marks: An Application to Vaccine Efficacy ⋮ Mark-specific hazard ratio model with missing multivariate marks ⋮ Profile local linear estimation of generalized semiparametric regression model for longitudinal data

Uses Software

• timereg

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Dynamic regression models for survival data.
• The 2-sample problem for failure rates depending on a continuous mark: an application to vaccine efficacy
• Two-Sample Tests of Cramér--von Mises- and Kolmogorov--Smirnov-Type for Randomly Censored Data
• A nonidentifiability aspect of the problem of competing risks.
• The Analysis of Failure Times in the Presence of Competing Risks
• Asymptotic Statistics
• Nonparametric estimation of the joint distribution of survival time and mark variables
• Checking the Cox model with cumulative sums of martingale-based residuals
• Local Linear Estimation for Time‐Dependent Coefficients in Cox's Regression Models
• Semiparametric Time-Varying Coefficients Regression Model for Longitudinal Data

This page was built for publication: Proportional hazards models with continuous marks