CSpace  > 应用数学研究所
Wang Xin1; Xue Xiaoming2; Zhou Jie3; Sun Liuquan2
Source Publicationactamathematicaeapplicataesinica
AbstractRare event data is encountered when the events of interest occur with low frequency, and the estimators based on the cohort data only may be inefficient. However, when external information is available for the estimation, the estimators utilizing external information can be more efficient. In this paper, we propose a method to incorporate external information into the estimation of the baseline hazard function and improve efficiency for estimating the absolute risk under the additive hazards model. The resulting estimators are shown to be uniformly consistent and converge weakly to Gaussian processes. Simulation studies demonstrate that the proposed method is much more efficient. An application to a bone marrow transplant data set is provided.
Document Type期刊论文
Affiliation1.School of Science,Beijing Information Science and Technology University
3.School of Mathematical Sciences,Capital Normal University
Recommended Citation
GB/T 7714
Wang Xin,Xue Xiaoming,Zhou Jie,et al. anefficientriskestimatorwithexternalinformationunderadditivehazardsmodel[J]. actamathematicaeapplicataesinica,2018,34(1):35.
APA Wang Xin,Xue Xiaoming,Zhou Jie,&Sun Liuquan.(2018).anefficientriskestimatorwithexternalinformationunderadditivehazardsmodel.actamathematicaeapplicataesinica,34(1),35.
MLA Wang Xin,et al."anefficientriskestimatorwithexternalinformationunderadditivehazardsmodel".actamathematicaeapplicataesinica 34.1(2018):35.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Wang Xin]'s Articles
[Xue Xiaoming]'s Articles
[Zhou Jie]'s Articles
Baidu academic
Similar articles in Baidu academic
[Wang Xin]'s Articles
[Xue Xiaoming]'s Articles
[Zhou Jie]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Wang Xin]'s Articles
[Xue Xiaoming]'s Articles
[Zhou Jie]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.