Efficient inferences for linear transformation models with doubly censored data

Author(s):  
Sangbum Choi ◽  
Xuelin Huang
2009 ◽  
Vol 9 (4) ◽  
pp. 321-343 ◽  
Author(s):  
Zhigang Zhang

In statistical analysis, when the value of a random variable is only known to be between two bounds, we say that this random variable is interval censored. This complicated censoring pattern is a common problem in research fields such as clinical trials or actuarial studies and raises challenges for statistical analysis. In this paper, we focus on regression analysis of case 2 interval-censored data. We first briefly review existing regression methods and an estimation approach under the class of linear transformation models developed by Zhang et al. We then propose a method for survival probability prediction via generalized estimating equations. We also consider a graphical model checking technique and a model selection tool. Some theoretical properties are established and the performance of our procedures is evaluated and illustrated by numerical studies including a real-life data analysis.


2018 ◽  
Vol 193 ◽  
pp. 42-54
Author(s):  
Huan Wang ◽  
Hongsheng Dai ◽  
Marialuisa Restaino ◽  
Yanchun Bao

2010 ◽  
Vol 17 (3) ◽  
pp. 347-372 ◽  
Author(s):  
Olga Julià ◽  
Guadalupe Gómez

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