Meta-regression is often used to form hypotheses about what is associated with heterogeneity in a meta-analysis and to estimate the extent to which effects can vary between cohorts and other distinguishing factors. However, study-level variables, called moderators, that are available and used in the meta-regression analysis will rarely explain all of the heterogeneity. Therefore, measuring and trying to understand residual heterogeneity is still important in a meta-regression, although it is not clear how some heterogeneity measures should be used in the meta-regression context. The coefficient of variation, and its variants, are useful measures of relative heterogeneity. We consider these measures in the context of meta-regression which allows researchers to investigate heterogeneity at different levels of the moderator and also average relative heterogeneity overall. We also provide CIs for the measures and our simulation studies show that these intervals have good coverage properties. We recommend that these measures and corresponding intervals could provide useful insights into moderators that may be contributing to the presence of heterogeneity in a meta-analysis and lead to a better understanding of estimated mean effects.
翻译:元递减常常被用来在元分析中就与异质性有关的内容形成假设,并估计不同组群和其他不同因素之间不同影响的程度;然而,现有和元递减分析中使用的研究级变数,即称为主持人,很少解释所有异质性;因此,衡量和试图了解剩余异质性在元递减中仍然很重要,尽管尚不清楚在元递减中应如何使用某些异质性措施。变异系数及其变异性是相对异性的有效衡量标准。我们认为,这些措施是在元递减背景下采取的,使研究人员能够调查不同级别主持人的异质性以及总体平均相对异质性。我们还提供了衡量指标,我们的模拟研究表明,这些间隔具有良好的覆盖性。我们建议,这些措施和相应的间隔可以向主持人提供有益的见解,从而可能有助于在元分析和导结果中更好地认识各种潜在影响。