VERIFICATION BIAS-IMPACT AND METHODS FOR CORRECTION WHEN ASSESSING ACCURACY OF DIAGNOSTIC TESTS

被引：0

作者：

Alonzo, Todd A. ^{[1
]}

机构：

[1] Univ So Calif, Dept Biostat, Los Angeles, CA 90089 USA

来源：

REVSTAT-STATISTICAL JOURNAL | 2014年 / 12卷 / 01期

关键词：

imputation; inverse probability weighting; ROC curve; sensitivity; specificity; OPERATING CHARACTERISTIC CURVES; MULTIPLE IMPUTATION; DISEASE VERIFICATION; ROC CURVES; AREA; SENSITIVITY; SPECIFICITY; ESTIMATORS; EFFICACY; SUBJECT;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Sometimes it is not feasible to obtain disease status verification for all study subejtcs. Analysis of only those with disease ascertainment can result in biased estimates of the accuracy (Sensitivity, specificity, ROC curve) of a diagnostic test, screening test, or boimarker if the estimation method does not properly account for the missing disease ascertainment. This paper discusses the impact of this bias, verification bias, when estimating the accuracy of dichotmous and continuous diagnostic tests. In addition, methods to correct for verification bias are described. Areas that require additional attention are also highlighted.

引用

页码：67 / 83

页数：17

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