Title

Outcome- and Auxiliary-Dependent Subsampling and Its Statistical Inference

Document Type

Article

Publication Date

2009

Keywords

Auxiliary variable, Biomarker, Outcome- and auxiliary-dependent subsampling, Population-based studies, Semiparametric empirical likelihood

Digital Object Identifier (DOI)

https://doi.org/10.1080/10543400903243025

Abstract

The performance of a biomarker predicting clinical outcome is often evaluated in a large prospective study. Due to high costs associated with bioassay, investigators need to select a subset from all available patients for biomarker assessment. We consider an outcome- and auxiliary-dependent subsampling (OADS) scheme, in which the probability of selecting a patient into the subset depends on the patient's clinical outcome and an auxiliary variable. We proposed a semiparametric empirical likelihood method to estimate the association between biomarker and clinical outcome. Asymptotic properties of the estimator are given. Simulation study shows that the proposed method outperforms alternative methods.

Was this content written or created while at USF?

Yes

Citation / Publisher Attribution

Journal of Biopharmaceutical Statistics, v. 19, issue 6, p. 1132-1150

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