论文标题
基于荟萃分析中的基于研究中的异质性测试
A Bootstrap Based Between-Study Heterogeneity Test in Meta-Analysis
论文作者
论文摘要
荟萃分析结合了现有研究的相关信息，以提供总体参数/效应大小的总体估计，并量化和解释研究之间的差异。但是，测试研究间的异质性是荟萃分析研究中最麻烦的主题之一。此外，没有提出任何方法来测试异质性的大小是否大于特定水平。现有方法（例如Q测试和似然比（LR）测试）因无法控制I型错误率和/或未能达到足够的统计能力而受到批评。尽管文献中已经提出了更好的参考分布近似值，但表达式很复杂，并且应用受到限制。在本文中，我们提出了基于自举的异质性测试，结合了限制的最大可能性（REML）比率测试或Q测试与Bootstrap程序，分别表示为B-reml-LRT和B-Q。进行了仿真研究，以检查和比较所提出的方法与常规LR测试，常规Q检验以及在随机效应荟萃分析和混合效应荟萃分析中的改进Q检验的性能。根据I型错误率和统计功率的结果，建议使用B-Q。提供了R软件包\ Mathtt {boot.heterogenenciention}，以促进所提出的方法的实现。
Meta-analysis combines pertinent information from existing studies to provide an overall estimate of population parameters/effect sizes, as well as to quantify and explain the differences between studies. However, testing the between-study heterogeneity is one of the most troublesome topics in meta-analysis research. Additionally, no methods have been proposed to test whether the size of the heterogeneity is larger than a specific level. The existing methods, such as the Q test and likelihood ratio (LR) tests, are criticized for their failure to control the Type I error rate and/or failure to attain enough statistical power. Although better reference distribution approximations have been proposed in the literature, the expression is complicated and the application is limited. In this article, we propose bootstrap based heterogeneity tests combining the restricted maximum likelihood (REML) ratio test or Q test with bootstrap procedures, denoted as B-REML-LRT and B-Q respectively. Simulation studies were conducted to examine and compare the performance of the proposed methods with the regular LR tests, the regular Q test, and the improved Q test in both the random-effects meta-analysis and mixed-effects meta-analysis. Based on the results of Type I error rates and statistical power, B-Q is recommended. An R package \mathtt{boot.heterogeneity} is provided to facilitate the implementation of the proposed method.
