论文标题
组合由二元结局的荟萃分析中的多个效应大小均匀性测试产生的依赖性p值
Combining dependent p-values resulting from multiple effect size homogeneity tests in meta-analysis for binary outcomes
论文作者
论文摘要
测试效果大小同质性是进行荟萃分析时的重要组成部分。在文献中发现了二进制结果的效果大小均匀性测试的比较研究，但没有一个绝对的胜利者。另一种方法是对相同的荟萃分析进行多效尺寸均匀性测试，并结合所得的依赖性p值。在本文中，我们将相关的兰开斯特方法应用于依赖统计检验。为了研究拟议方法的性能，我们在案例研究和模拟数据集上应用了八个不同的效应大小均匀性测试，并将结果结合在一起。当研究数量较小时，该方法在存在效应大小的情况下，基于得分函数的测试的性能与测试的性能相似，但是随着研究数量的增加，这些测试的表现要优于这些测试。但是，该方法的性能对相关测试之间假定的相关系数值敏感，并且仅在此值较高时性能很好。在效果大小均匀性测试的情况下，需要进行更多的研究来研究该方法对相关性的假设，并研究该方法在连续结果的荟萃分析中的性能。
Testing effect size homogeneity is an essential part when conducting a meta-analysis. Comparative studies of effect size homogeneity tests in case of binary outcomes are found in the literature, but no test has come out as an absolute winner. A alternative approach would be to carry out multiple effect size homogeneity tests on the same meta-analysis and combine the resulting dependent p-values. In this article we applied the correlated Lancaster method for dependent statistical tests. To investigate the proposed approach's performance, we applied eight different effect size homogeneity tests on a case study and on simulated datasets, and combined the resulting p-values. The proposed method has similar performance to that of tests based on the score function in the presence of a effect size when the number of studies is small, but outperforms these tests as the number of studies increases. However, the method's performance is sensitive to the correlation coefficient value assumed between dependent tests, and only performs well when this value is high. More research is needed to investigate the method's assumptions on correlation in case of effect size homogeneity tests, and to study the method's performance in meta-analysis of continuous outcomes.
