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在丰富性研究中的预测值的倾斜度校正的信心区间

Dadong Zhang¹, Jingye Wang¹, Suqin Cai¹

¹Biostatistics, Illumina Inc., San Diego, California, USA.

Statistics in medicine

|November 20, 2024

概括

对正预测值 (PPV) 和负预测值 (NPV) 的置信区间的估计在丰富研究中具有挑战性. 在这些场景中,Gart & Nam (GN) 和MoverJ方法显示了提高准确性的前景.

科学领域:

生物统计学生物统计学
流行病学流行病学
医学诊断医学诊断医学诊断

背景情况:

阳性预测值 (PPV) 和负预测值 (NPV) 是诊断测试评估中的关键指标.
计算PPV和NPV的置信区间 (CI) 在前性研究中很简单,但在诸如病例控制研究等丰富设计中具有挑战性,因为疾病患病率不同.
极端状况,如疾病流行率非常低或很高,加剧了CI估计的困难.

研究的目的:

在缩研究中扩展现有计算PPV和NPVCI的方法.
在具有挑战性的条件下评估PPV和NPV估计的新CI方法.

主要方法:

该研究扩展了Li的方法,从二项式比例CI的比率中推导PPV和NPVCI.
探索并转换了用于PPV和NPV的二项式比例的额外CI方法,包括Gart & Nam (GN),MoverJ和Walter.
进行了模拟,以比较这些扩展方法的性能与既有方法 (Fieller,Pepe,Delta) 在斜率和覆盖率方面的表现.

主要成果:

没有一种单一的方法在所有场景中证明了通用最佳性.
与其他方法相比,Gart & Nam (GN) 和MoverJ方法在斜率和覆盖率方面普遍表现良好.
这些方法在缩研究中为PPV和NPV提供了改进的CI估计,特别是在极端条件下.

结论:

在缩研究中,建议使用Gart & Nam (GN) 和MoverJ方法来计算PPV和NPV的置信区间.
这些方法提供了更可靠的估计,解决了不同疾病患病率和极端条件所带来的挑战.
进一步的研究可能会探索额外的方法或改进,以进行可靠的诊断准确性评估.

关键词:

信心区间的时间间隔是信任区间.覆盖范围覆盖范围的覆盖范围.预测值是指预测值的值.两个二项式比例的比率.歪歪的歪歪的歪歪的

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