Semiparametric linear transformation models for current status data

2005 ◽  
Vol 33 (1) ◽  
pp. 85-96 ◽  
Author(s):  
Jianguo Sun ◽  
Liuquan Sun
Keyword(s):  
Linear Transformation ◽  
Current Status Data ◽  
Current Status ◽  
Transformation Models ◽  
Linear Transformation Models ◽  
Status Data

Efficient estimation of a linear transformation model for current status data via penalized splines

2018 ◽  
Vol 29 (1) ◽  
pp. 3-14
Author(s):  
Minggen Lu ◽  
Yan Liu ◽  
Chin-Shang Li
Keyword(s):  
Linear Transformation ◽  
Penalized Splines ◽  
Efficient Estimation ◽  
Current Status Data ◽  
Transformation Model ◽  
Current Status ◽  
Finite Sample ◽  
Computationally Efficient ◽  
Linear Transformation Model ◽  
Status Data

We propose a flexible and computationally efficient penalized estimation method for a semi-parametric linear transformation model with current status data. To facilitate model fitting, the unknown monotone function is approximated by monotone B-splines, and a computationally efficient hybrid algorithm involving the Fisher scoring algorithm and the isotonic regression is developed. A goodness-of-fit test and model diagnostics are also considered. The asymptotic properties of the penalized estimators are established, including the optimal rate of convergence for the function estimator and the semi-parametric efficiency for the regression parameter estimators. An extensive numerical experiment is conducted to evaluate the finite-sample properties of the penalized estimators, and the methodology is further illustrated with two real studies.

Semiparametric transformation models for current status data with informative censoring

2012 ◽  
Vol 54 (5) ◽  
pp. 641-656 ◽  
Author(s):  
Chyong-Mei Chen ◽  
Tai-Fang C. Lu ◽  
Man-Hua Chen ◽  
Chao-Min Hsu
Keyword(s):  
Informative Censoring ◽  
Current Status Data ◽  
Current Status ◽  
Transformation Models ◽  
Semiparametric Transformation ◽  
Status Data

Regression analysis of informative current status data with the additive hazards model

2014 ◽  
Vol 21 (2) ◽  
pp. 241-258 ◽  
Author(s):  
Shishun Zhao ◽  
Tao Hu ◽  
Ling Ma ◽  
Peijie Wang ◽  
Jianguo Sun
Keyword(s):  
Regression Analysis ◽  
Current Status Data ◽  
Current Status ◽  
Additive Hazards Model ◽  
Additive Hazards ◽  
Hazards Model ◽  
Status Data
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