New Confidence Intervals for Relative Risk of Two Correlated Proportions.
New Confidence Intervals for Relative Risk of Two Correlated Proportions.
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DOI：
10.1007/s12561-022-09345-7
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发表时间：
2023
影响因子：
1
通讯作者：
Shan G
中科院分区：
文献类型：
--
作者：
DelRocco N;Wang Y;Wu D;Yang Y;Shan G
生物医学研究，如临床试验，通常需要比较两个相关测试的测量结果，其中每个观察单位通过相对风险与感兴趣的二元结果相关联。相关的置信区间是至关重要的，因为它提供了一个可能值的谱的评价，允许相对风险的更可靠的解释。在相对风险的可用置信区间方法中，渐近分数区间是最广泛推荐用于实际应用的方法。我们提出了一个修改的相对风险的分数区间，我们还扩展了现有的非参数U-统计量为基础的相对风险的置信区间。此外，我们从理论上证明了原来的渐近分数区间是等价的Nam和Blackwelder提出的约束最大似然区间。两个临床相关的肿瘤学试验被用来证明我们的方法的真实世界的性能。新方法的有限样本性质，目前的实践标准，和其他替代品进行了研究，通过广泛的模拟研究。我们发现，随着相关性强度的增加，当样本量不太大时，新的基于分数的区间在覆盖概率方面优于现有的区间。此外，我们的研究结果表明，新的非参数区间提供的覆盖范围，最一致地满足或超过标称覆盖概率。
Biomedical studies, such as clinical trials, often require the comparison of measurements from two correlated tests in which each unit of observation is associated with a binary outcome of interest via relative risk. The associated confidence interval is crucial because it provides an appreciation of the spectrum of possible values, allowing for a more robust interpretation of relative risk. Of the available confidence interval methods for relative risk, the asymptotic score interval is the most widely recommended for practical use. We propose a modified score interval for relative risk and we also extend an existing nonparametric U-statistic-based confidence interval to relative risk. In addition, we theoretically prove that the original asymptotic score interval is equivalent to the constrained maximum likelihood-based interval proposed by Nam and Blackwelder. Two clinically relevant oncology trials are used to demonstrate the real-world performance of our methods. The finite sample properties of the new approaches, the current standard of practice, and other alternatives are studied via extensive simulation studies. We show that, as the strength of correlation increases, when the sample size is not too large the new score-based intervals outperform the existing intervals in terms of coverage probability. Moreover, our results indicate that the new nonparametric interval provides the coverage that most consistently meets or exceeds the nominal coverage probability.