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Author:

Wu Mixia (Wu Mixia.) | Zhang Xiaoyu (Zhang Xiaoyu.) | Zhang Wei (Zhang Wei.) | Zhang Xu (Zhang Xu.) | Liu Aiyi (Liu Aiyi.)

Indexed by:

PubMed

Abstract:

This article concerns evaluating the effectiveness of a continuous diagnostic biomarker against a continuous gold standard that is measured with error. Extending the work of Obuchowski (2005, 2016), Wu et al (2016) suggested an accuracy index and proposed an estimator for the index with error-prone standard when the reliability coefficient is known. Combining with additional measurements (without measurement errors) on the continuous gold standard collected from some subjects, this article proposes two adaptive estimators of the accuracy index when the reliability coefficient is unknown, and further establish the consistency and asymptotic normality of these estimators. Simulation studies are conducted to compare various estimators. Data from an intervention trial on glycemic control among children with type 1 diabetes are used to illustrate the proposed methods.

Keyword:

additive errors diagnostic accuracy asymptotic normality reliability coefficient adaptive estimation measurement errors biomarkers

Author Community:

  • [ 1 ] [Wu Mixia]College of Statistics and Data Science, Beijing University of Technology, Beijing, China
  • [ 2 ] [Zhang Xiaoyu]College of Statistics and Data Science, Beijing University of Technology, Beijing, China
  • [ 3 ] [Zhang Wei]LSC, NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
  • [ 4 ] [Zhang Xu]College of Statistics and Data Science, Beijing University of Technology, Beijing, China
  • [ 5 ] [Liu Aiyi]Biostatistics and Bioinformatics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, Maryland, USA

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Source :

Statistics in medicine

ISSN: 1097-0258

Year: 2021

Issue: 4

Volume: 40

Page: 1034-1058

2 . 0 0 0

JCR@2022

ESI HC Threshold:53

JCR Journal Grade:1

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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