A semiparametric inverse‐Gaussian model and inference for survival data with a cured proportion

DOI10.1002/cjs.11226zbMath1306.62213OpenAlexW2091819253MaRDI QIDQ5175767

Kjell A. Doksum, Janice N. Cormier, Sangbum Choi, Xuelin Huang

Publication date: 25 February 2015

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/cjs.11226

zbMATH Keywords

Wiener processtransformation modelthreshold regressionnonparametric likelihooddegradation modelimproper distributionfirst-hitting-time

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Reliability and life testing (62N05)

Related Items (2)

Semi-parametric survival analysis via Dirichlet process mixtures of the first hitting time model ⋮ Estimating duration distribution aided by auxiliary longitudinal measures in presence of missing time origin

Cites Work

• Unnamed Item
• Proportional hazards and threshold regression: their theoretical and practical connections
• Review and implementation of cure models based on first hitting times for Wiener processes
• Accelerated degradation models for failure based on geometric Brownian motion and gamma processes
• Wiener processes with random effects for degradation data
• Understanding the shape of the hazard rate: A process point of view. (With comments and a rejoinder).
• Gaussian models for degradation processes. I: Methods for the analysis of biomarker data
• Threshold regression for survival analysis: modeling event times by a stochastic process reaching a boundary
• Checking semiparametric transformation models with censored data
• On semiparametric transformation cure models
• Weighted Breslow-type and maximum likelihood estimation in semiparametric transformation models
• Checking the Cox model with cumulative sums of martingale-based residuals
• A Nonparametric Mixture Model for Cure Rate Estimation
• A General Class of Semiparametric Transformation Frailty Models for Nonproportional Hazards Survival Data
• Analysing Competing Risks Data With Transformation Models
• Semiparametric Transformation Models for Survival Data With a Cure Fraction
• Estimation in degradation models with explanatory variables
• Models for Variable-Stress Accelerated Life Testing Experiments Based on Wiener Processes and the Inverse Gaussian Distribution

This page was built for publication: A semiparametric inverse‐Gaussian model and inference for survival data with a cured proportion