JASA
Jan 05, 2026
SurvSTAAR: A powerful statistical framework for rare variant analysis of time-to-event traits in large-scale whole-genome sequencing studies
Authors
Yidan Cui
Shiyang Ma
Yuxin Yuan
Nengjie Zhu
Haifeng Chen
Ting Wei
Zilin Li
Xihao Li
Zhangsheng Yu
Research Topics
Machine Learning
Survival Analysis
Paper Information
-
Journal:
Journal of the American Statistical Association -
DOI:
10.1080/01621459.2025.2606388 -
Published:
January 05, 2026 -
Added to Tracker:
Feb 10, 2026
Author Details
Yidan Cui
AuthorShiyang Ma
AuthorYuxin Yuan
AuthorNengjie Zhu
AuthorHaifeng Chen
AuthorTing Wei
AuthorZilin Li
AuthorXihao Li
AuthorZhangsheng Yu
AuthorResearch Topics & Keywords
Machine Learning
Research AreaSurvival Analysis
Research AreaCitation Information
APA Format
Yidan Cui
,
Shiyang Ma
,
Yuxin Yuan
,
Nengjie Zhu
,
Haifeng Chen
,
Ting Wei
,
Zilin Li
,
Xihao Li
&
Zhangsheng Yu
(2026)
.
SurvSTAAR: A powerful statistical framework for rare variant analysis of time-to-event traits in large-scale whole-genome sequencing studies.
Journal of the American Statistical Association
, 10.1080/01621459.2025.2606388.
BibTeX Format
@article{paper779,
title = { SurvSTAAR: A powerful statistical framework for rare variant analysis of time-to-event traits in large-scale whole-genome sequencing studies },
author = {
Yidan Cui
and Shiyang Ma
and Yuxin Yuan
and Nengjie Zhu
and Haifeng Chen
and Ting Wei
and Zilin Li
and Xihao Li
and Zhangsheng Yu
},
journal = { Journal of the American Statistical Association },
year = { 2026 },
doi = { 10.1080/01621459.2025.2606388 },
url = { https://doi.org/10.1080/01621459.2025.2606388 }
}