首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Inference on semiparametric transformation model with general interval-censored failure time data
Authors:Peijie Wang  Mingyue Du  Jianguo Sun
Institution:1. School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, People's Republic of China;2. Center for Applied Statistical Research, School of Mathematics, Jilin University, Changchun, People's Republic of China;3. Center for Applied Statistical Research, School of Mathematics, Jilin University, Changchun, People's Republic of China;4. Department of Statistics, University of Missouri, Columbia, MI, USA
Abstract:Failure time data occur in many areas and in various censoring forms and many models have been proposed for their regression analysis such as the proportional hazards model and the proportional odds model. Another choice that has been discussed in the literature is a general class of semiparmetric transformation models, which include the two models above and many others as special cases. In this paper, we consider this class of models when one faces a general type of censored data, case K informatively interval-censored data, for which there does not seem to exist an established inference procedure. For the problem, we present a two-step estimation procedure that is quite flexible and can be easily implemented, and the consistency and asymptotic normality of the proposed estimators of regression parameters are established. In addition, an extensive simulation study is conducted and suggests that the proposed procedure works well for practical situations. An application is also provided.
Keywords:Case K interval-censored data  informative censoring  model checking  transformation model  sieve maximum likelihood estimation
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号