Recent progresses in outcome-dependent sampling with failure time data

被引:0
作者
Jieli Ding
Tsui-Shan Lu
Jianwen Cai
Haibo Zhou
机构
[1] Wuhan University,School of Mathematics and Statistics
[2] National Taiwan Normal University,Department of Mathematics
[3] University of North Carolina at Chapel Hill,Department of Biostatistics
来源
Lifetime Data Analysis | 2017年 / 23卷
关键词
Case–cohort design; ODS design; Failure time data;
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学科分类号
摘要
An outcome-dependent sampling (ODS) design is a retrospective sampling scheme where one observes the primary exposure variables with a probability that depends on the observed value of the outcome variable. When the outcome of interest is failure time, the observed data are often censored. By allowing the selection of the supplemental samples depends on whether the event of interest happens or not and oversampling subjects from the most informative regions, ODS design for the time-to-event data can reduce the cost of the study and improve the efficiency. We review recent progresses and advances in research on ODS designs with failure time data. This includes researches on ODS related designs like case–cohort design, generalized case–cohort design, stratified case–cohort design, general failure-time ODS design, length-biased sampling design and interval sampling design.
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页码:57 / 82
页数:25
相关论文
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