Outcome- and auxiliary-dependent subsampling and its statistical inference.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Wang, X; Wu, Y; Zhou, H

Published Date

  • November 2009

Published In

Volume / Issue

  • 19 / 6

Start / End Page

  • 1132 - 1150

PubMed ID

  • 20183468

Pubmed Central ID

  • 20183468

Electronic International Standard Serial Number (EISSN)

  • 1520-5711

Digital Object Identifier (DOI)

  • 10.1080/10543400903243025

Language

  • eng

Conference Location

  • England