|Title||Recent progresses in outcome-dependent sampling with failure time data.|
|Publication Type||Journal Article|
|Year of Publication||2017|
|Authors||Ding, Jieli, Tsui-Shan Lu, Jianwen Cai, and Haibo Zhou|
|Journal||Lifetime Data Anal|
|Date Published||2017 Jan|
|Keywords||Humans, Probability, Research Design, Retrospective Studies|
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.
|Alternate Journal||Lifetime Data Anal|
|Original Publication||Recent progresses in outcome-dependent sampling with failure time data.|
|PubMed Central ID||PMC4942414|
|Grant List||P01 CA142538 / CA / NCI NIH HHS / United States |
R01 ES021900 / ES / NIEHS NIH HHS / United States
Recent progresses in outcome-dependent sampling with failure time data.