Conditional independence test of failure and truncation times: essential tool for method selection
From MaRDI portal
Publication:2076161
DOI10.1016/j.csda.2021.107402OpenAlexW3216180171MaRDI QIDQ2076161
Hong Zhu, Daewoo Pak, Jing Qin, Jing Ning
Publication date: 18 February 2022
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2021.107402
right censoringconditional independenceleft truncationCox proportional hazards modelconditional generalized odds ratio
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Parametric likelihood inference and goodness-of-fit for dependently left-truncated data, a copula-based approach
- Testing quasi-independence for truncation data
- Cox's regression model for counting processes: A large sample study
- Some new constructions of bivariate Weibull models
- Testing conditional independence using maximal nonlinear conditional correlation
- Rank regression methods for left-truncated and right-censored data
- Nonparametric and semiparametric regression estimation for length-biased survival data
- Testing the assumption of independence of truncation time and failure time
- The Robust Inference for the Cox Proportional Hazards Model
- A note on the product-limit estimator under right censoring and left truncation
- Nonparametric analysis of truncated survival data, with application to AIDS
- A Proportional Hazards Model for Arbitrarily Censored and Truncated Data
- Regression Analysis Under Non-standard Situations: A Pairwise Pseudolikelihood Approach
- CHARACTERISTIC FUNCTION BASED TESTING FOR CONDITIONAL INDEPENDENCE: A NONPARAMETRIC REGRESSION APPROACH
- Analysis of dependently truncated data in Cox framework
- Generalized instrumental inequalities: testing the instrumental variable independence assumption
- A general class of quasi-independence tests for left-truncated right-censored data
- Statistical Models for Prevalent Cohort Data
- Transition Models for Multivariate Longitudinal Binary Data
- Semiparametric maximum likelihood inference for truncated or biased-sampling data
- Testing Quasi-Independence of Failure and Truncation Times via Conditional Kendall's Tau
