Recent progresses in outcome-dependent sampling with failure time data

Jieli Ding, Tsui Shan Lu, Jianwen Cai, Haibo Zhou*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)57-82
Number of pages26
JournalLifetime Data Analysis
Issue number1
Publication statusPublished - 2017 Jan 1


  • Case–cohort design
  • Failure time data
  • ODS design

ASJC Scopus subject areas

  • Applied Mathematics


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