Exact inference for the Youden index to discriminate individuals using two-parameter exponentially distributed pooled samples

Q3 Medicine
Sumith Gunasekera, Lakmali Weerasena, Aruna Saram, O. Ajumobi
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引用次数: 1

Abstract

It has become increasingly common in epidemiological studies to pool specimens across subjects as a useful cot-cutting technique to achieve accurate quantification of biomarkers and certain environmental chemicals. The data collected from these pooled samples can then be utilized to estimate the Youden Index, which measures biomarker's effectiveness and aids in the selection of an optimal threshold value, as a summary measure of the Receiver Operating Characteristic curve. The aim of this paper is to make use of generalized approach to estimate and testing of the Youden index. This goal is accomplished by the comparison of classical and generalized procedures for the Youden Index with the aid of pooled samples from the shifted-exponentially distributed biomarkers for the low-risk and high-risk patients. These are juxtaposed using confidence intervals, p-values, power of the test, size of the test, and coverage probability with a wide-ranging simulation study featuring a selection of various scenarios. In order to demonstrate the advantages of the proposed generalized procedures over its classical counterpart, an illustrative example is discussed using the Duchenne Muscular Dystrophy data available at http://biostat.mc.vanderbilt.edu/wiki/Main/DataSets or http://lib.stat.cmu.edu/datasets/.
使用双参数指数分布的混合样本对约登指数进行区分个体的精确推断
在流行病学研究中,将不同对象的标本汇集起来作为一种有用的裁剪技术,以实现生物标志物和某些环境化学物质的准确定量,这已经变得越来越普遍。然后,从这些汇集的样本中收集的数据可用于估计约登指数,该指数测量生物标志物的有效性,并有助于选择最佳阈值,作为接受者工作特征曲线的汇总测量。本文的目的是利用广义方法来估计和检验约登指数。这一目标是通过比较约登指数的经典和通用程序,并借助于低风险和高风险患者的指数分布生物标志物的汇集样本来实现的。这些并置使用置信区间,p值,测试的能力,测试的大小和覆盖概率与广泛的模拟研究,以选择各种场景为特征。为了证明所提出的广义程序相对于其经典对应程序的优势,使用可在http://biostat.mc.vanderbilt.edu/wiki/Main/DataSets或http://lib.stat.cmu.edu/datasets/上获得的杜氏肌营养不良症数据讨论了一个示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biostatistics and Epidemiology
Biostatistics and Epidemiology Medicine-Health Informatics
CiteScore
1.80
自引率
0.00%
发文量
23
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