论文标题
用于网络荟萃分析和调整置信区间的易于置信区间公式
Easy confidence interval formulas for network meta-analysis and adjustment of confidence intervals for a small number of studies
论文作者
论文摘要
我们提出了有关WALD统计量，似然比统计量的置信区间的简单公式，以及网络荟萃分析的得分统计量。此外，我们考虑了有关少量研究的网络荟萃分析的问题，因此无法保持名义置信度。对于少量研究的分析中的偏差调整，Bartlett型调整是一种众所周知的方法。许多Bartlett型调整型方法基于最大似然估计器。但是，网络荟萃分析通常使用尚未在Bartlett-type调整中进行广泛讨论的受限最大似然估计器。在本文中，我们为WALD统计量，似然比统计量和得分统计量提出了一种Bartlett-Type调整方法，当令人讨厌的参数不仅通过最大似然法估算，还包括受限制的最大似然方法。此外，我们通过将引导方法应用于Bartlett-Type调整后的统计数据来提出高阶调整。使用计算机模拟，我们确认调整后的置信区间保持了名义置信度。此外，我们确认了基于限制的最大似然法的置信区间测试的置信区间在没有进一步调整的情况下表现良好。最后，我们证明了对实际网络荟萃分析调整置信区间。
We propose simple formulas of confidence intervals for the Wald statistic, likelihood ratio statistic, and score statistic for a network meta-analysis. In addition, we consider resolutions for concerns that network meta-analyses with a small number of studies cannot hold a nominal confidence level. For a bias adjustment in analyses with a small number of studies, a Bartlett-type adjustment is a well-known method. Many Bartlett-type adjustment-type methods are based on maximum likelihood estimators. However, the network meta-analysis often uses the restricted maximum likelihood estimators that have not been extensively discussed in Bartlett-type adjustment. In this paper, we propose a Bartlett-type adjustment method for the Wald statistic, likelihood ratio statistic, and score statistic when nuisance parameters are estimated by not only the maximum likelihood method but also the restricted maximum likelihood method. In addition, we propose a higher-order adjustment by applying the bootstrap method to the Bartlett-type adjusted statistics. Using a computer simulation, we confirmed that the adjusted confidence intervals maintained a nominal confidence level. In addition, we confirmed that the confidence interval of the likelihood ratio test based on the restricted maximum likelihood method performs well without further bootstrap adjustment. Finally, we demonstrated that confidence intervals were adjusted for actual network meta-analysis.
