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Inference on semiparametric transformation model with general interval-censored failure time data

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成果类型:
期刊论文
作者:
Wang, Peijie;Zhao, Hui*;Du, Mingyue;Sun, Jianguo
通讯作者:
Zhao, Hui
作者机构:
[Wang, Peijie] Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China.
[Wang, Peijie; Du, Mingyue] Jilin Univ, Ctr Appl Stat Res, Sch Math, Changchun, Jilin, Peoples R China.
[Zhao, Hui] Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Hubei, Peoples R China.
[Sun, Jianguo] Univ Missouri, Dept Stat, Columbiaville, MI USA.
通讯机构:
[Zhao, Hui] C
Cent China Normal Univ, Sch Math & Stat, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
关键词:
Case K interval-censored data;informative censoring;model checking;sieve maximum likelihood estimation;transformation model
期刊:
Journal of Nonparametric Statistics
ISSN:
1048-5252
年:
2018
卷:
30
期:
3
页码:
758-773
基金类别:
This work was partly supported by the National Natural Science Foundation of China Grant Nos. 11731011, 11671168, 11471135, 11571133 and the self determined research funds of CCNU from the college’s basic research of MOE (CCNU15ZD011, CCNU16JCZX11).
机构署名:
本校为通讯机构
院系归属:
数学与统计学学院
摘要:
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 proc...

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