title: Recent progresses in outcome-dependent sampling with failure time data.
abstract: 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.
authors.affiliation: School of Mathematics and Statistics, Wuhan University, Wuhan, Hubei, 430072, China.
authors.forename: Jieli
authors.initials: J
authors.lastname: Ding
authors.affiliation: Department of Mathematics, National Taiwan Normal University, Taipei, 116, Taiwan.
authors.forename: Tsui-Shan
authors.initials: TS
authors.lastname: Lu
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
authors.forename: Jianwen
authors.initials: J
authors.lastname: Cai
authors.affiliation: Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. zhou@bios.unc.edu.
authors.forename: Haibo
authors.initials: H
authors.lastname: Zhou
mesh_terms: D006801:Humans; D011336:Probability; D012107:Research Design; D012189:Retrospective Studies
keywords: Case–cohort design; Failure time data; ODS design