A class of tests of proportional hazards assumption for left-truncated and right-censored data
From MaRDI portal
Publication:5130341
DOI10.1080/02664763.2015.1027884OpenAlexW2060370577MaRDI QIDQ5130341
Wei Chen, Yan-Feng Li, De-Hui Wang
Publication date: 4 November 2020
Published in: Journal of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02664763.2015.1027884
counting processtwo-sample problemleft-truncated and right-censored dataproportional hazards assumptionhazard ratio
Related Items (2)
Bootstrap and permutation rank tests for proportional hazards under right censoring ⋮ The wild bootstrap for multivariate Nelson-Aalen estimators
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Cox's regression model for counting processes: A large sample study
- Estimation and goodness-of-fit for the Cox model with various types of censored data
- A class of rank-based test for left-truncated and right-censored data
- Rank regression methods for left-truncated and right-censored data
- Survival analysis. Techniques for censored and truncated data.
- Goodness-of-fit criteria for the Cox model from left truncated and right censored data
- A class of rank test procedures for censored survival data
- Goodness-of-Fit Analysis for the Cox Regression Model Based on a Class of Parameter Estimators
- A simple test of the proportional hazards assumption
- A note on the product-limit estimator under right censoring and left truncation
- Product limit estimates: a generalized maximum likelihood study
- Nonparametric analysis of truncated survival data, with application to AIDS
- Chi-squared goodness-of-fit tests for the proportional hazards regression model
- Checking the Cox model with cumulative sums of martingale-based residuals
- Testing for the Proportionality of Hazards in Two Samples Against the Increasing Cumulative Hazard Ratio Alternative
- Estimating a distribution function with truncated data
This page was built for publication: A class of tests of proportional hazards assumption for left-truncated and right-censored data
