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Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data.

Abstract

We propose a two-stage outcome-dependent sampling design and inference procedure for studies that concern interval-censored failure time outcomes. This design enhances the study efficiency by allowing the selection probabilities of the second-stage sample, for which the expensive exposure variable is ascertained, to depend on the first-stage observed interval-censored failure time outcomes. In particular, the second-stage sample is enriched by selectively including subjects who are known or observed to experience the failure at an early or late time. We develop a sieve semiparametric maximum pseudo likelihood procedure that makes use of all available data from the proposed two-stage design. The resulting regression parameter estimator is shown to be consistent and asymptotically normal, and a consistent estimator for its asymptotic variance is derived. Simulation results demonstrate that the proposed design and inference procedure performs well in practical situations and is more efficient than the existing designs and methods. An application to a phase 3 HIV vaccine trial is provided.

Authors+Show Affiliations

Department of Mathematics and Statistics, University of North Carolina at Charlotte, Fretwell 335L, 9201 University City Blvd., Charlotte, NC, 28223, USA. qzhou8@uncc.edu.Department of Biostatistics, University of North Carolina at Chapel Hill, 3101D McGavran-Greenberg Hall, Chapel Hill, NC, 27599, USA.Department of Biostatistics, University of North Carolina at Chapel Hill, 3104C McGavran-Greenberg Hall, Chapel Hill, NC, 27599, USA.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30617753

Citation

Zhou, Qingning, et al. "Semiparametric Inference for a Two-stage Outcome-dependent Sampling Design With Interval-censored Failure Time Data." Lifetime Data Analysis, 2019.
Zhou Q, Cai J, Zhou H. Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data. Lifetime Data Anal. 2019.
Zhou, Q., Cai, J., & Zhou, H. (2019). Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data. Lifetime Data Analysis, doi:10.1007/s10985-019-09461-5.
Zhou Q, Cai J, Zhou H. Semiparametric Inference for a Two-stage Outcome-dependent Sampling Design With Interval-censored Failure Time Data. Lifetime Data Anal. 2019 Jan 7; PubMed PMID: 30617753.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Semiparametric inference for a two-stage outcome-dependent sampling design with interval-censored failure time data. AU - Zhou,Qingning, AU - Cai,Jianwen, AU - Zhou,Haibo, Y1 - 2019/01/07/ PY - 2017/11/27/received PY - 2019/01/02/accepted PY - 2020/07/07/pmc-release PY - 2019/1/9/entrez PY - 2019/1/9/pubmed PY - 2019/1/9/medline KW - Bernstein polynomial KW - Biased sampling KW - Missing data KW - Proportional hazards model KW - Sieve estimation JF - Lifetime data analysis JO - Lifetime Data Anal N2 - We propose a two-stage outcome-dependent sampling design and inference procedure for studies that concern interval-censored failure time outcomes. This design enhances the study efficiency by allowing the selection probabilities of the second-stage sample, for which the expensive exposure variable is ascertained, to depend on the first-stage observed interval-censored failure time outcomes. In particular, the second-stage sample is enriched by selectively including subjects who are known or observed to experience the failure at an early or late time. We develop a sieve semiparametric maximum pseudo likelihood procedure that makes use of all available data from the proposed two-stage design. The resulting regression parameter estimator is shown to be consistent and asymptotically normal, and a consistent estimator for its asymptotic variance is derived. Simulation results demonstrate that the proposed design and inference procedure performs well in practical situations and is more efficient than the existing designs and methods. An application to a phase 3 HIV vaccine trial is provided. SN - 1572-9249 UR - https://www.unboundmedicine.com/medline/citation/30617753/Semiparametric_inference_for_a_two_stage_outcome_dependent_sampling_design_with_interval_censored_failure_time_data_ L2 - https://doi.org/10.1007/s10985-019-09461-5 DB - PRIME DP - Unbound Medicine ER -