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Global hypothesis test to compare the likelihood ratios of multiple binary diagnostic tests with ignorable missing data

机译:全局假设检验,用于比较多个二进制诊断检验与可忽略的缺失数据的似然比

摘要

In this article, a global hypothesis test is studied to simultaneously compare the likelihood ratios of multiple binary diagnostic tests when in the presence of partial disease verification the missing data mechanism is ignorable. The hypothesis test is based on the chi-squared distribution. Simulation experiments were carried out to study the type I error and the power of the global hypothesis test when comparing the likelihood ratios of two and three diagnostic tests respectively. The results obtained were applied to the diagnosis of coronary stenosis.
机译:本文对全局假设检验进行了研究,以在存在部分疾病验证且缺少数据机制可忽略的情况下,同时比较多个二元诊断检验的似然比。假设检验基于卡方分布。当分别比较两个和三个诊断测试的似然比时,进行了模拟实验以研究I型错误和全局假设测试的功效。获得的结果可用于诊断冠状动脉狭窄。

著录项

  • 作者

    Marín Jimenez Ana Eugenia;

  • 作者单位
  • 年度 2014
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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