Outcome- and auxiliary-dependent subsampling and its statistical inference.
Journal Article (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