Linear transformation models for censored data under truncation
DOI10.1016/J.JSPI.2017.07.006zbMath1377.62187OpenAlexW2748180645MaRDI QIDQ1681047
Marialuisa Restaino, Huan Wang, Yanchun Bao, Hongsheng Dai
Publication date: 17 November 2017
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: http://discovery.dundee.ac.uk/ws/files/18616823/Huan_LTM_SPI.pdf
truncationsurvival analysiscensoringbivariate survival functionlinear transformation modelsemiparametric linear transformation model
Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)
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Cites Work
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- A polar coordinate transformation for estimating bivariate survival functions with randomly censored and truncated data
- An inverse probability weighted estimator for the bivariate distribution function under right censoring
- Nonparametric estimation of the bivariate survival function with left-truncated and right-censored data
- Kaplan-Meier estimate on the plane
- Kaplan-Meier estimate on the plane: Weak convergence, LIL, and the bootstrap
- Bivariate distribution and hazard functions when a component is randomly truncated
- Nonparametric estimation of the bivariate survival function with truncated data
- An inverse-probability-weighted approach to estimation of the bivariate survival function under left-truncation and right-censoring
- Semiparametric regression analysis for clustered failure time data
- A class of nonparametric bivariate survival function estimators for randomly censored and truncated data
- Estimation and Testing in a Two-Sample Generalized Odds-Rate Model
- Miscellanea. On the linear transformation model for censored data
- Bivariate Estimation With Right-Truncated Data
- Predicting Survival Probabilities With Semiparametric Transformation Models
- Maximum Likelihood Estimation in the Proportional Odds Model
- Rank-based regression for analysis of repeated measures
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