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Methods to calculate uncertainty in the estimated overall effect size from a random-effects meta-analysis

机译:通过随机效应荟萃分析计算估计总体效应大小的不确定性的方法

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摘要

Meta-analyses are an important tool within systematic reviews to estimate the overall effect size and its confidence interval for an outcome of interest. If heterogeneity between the results of the relevant studies is anticipated, then a random-effects model is often preferred for analysis. In this model, a prediction interval for the true effect in a new study also provides additional useful information. However, the DerSimonian and Laird method-frequently used as the default method for meta-analyses with random effects-has been long challenged due to its unfavorable statistical properties. Several alternative methods have been proposed that may have better statistical properties in specific scenarios. In this paper, we aim to provide a comprehensive overview of available methods for calculating point estimates, confidence intervals, and prediction intervals for the overall effect size under the random-effects model. We indicate whether some methods are preferable than others by considering the results of comparative simulation and real-life data studies.
机译:荟萃分析是系统评价中重要的工具,可用来评估整体效果的大小及其对感兴趣结果的置信区间。如果预期相关研究结果之间存在异质性,则通常首选随机效应模型进行分析。在此模型中,新研究中真实作用的预测间隔也提供了更多有用的信息。但是,DerSimonian和Laird方法(经常用作具有随机效应的荟萃分析的默认方法)由于其不利的统计特性而长期受到挑战。已经提出了几种在特定情况下可能具有更好的统计属性的替代方法。在本文中,我们旨在提供一种在随机效应模型下计算总体效应量的点估计,置信区间和预测区间的可用方法的全面概述。通过比较仿真和实际数据研究的结果,我们表明某些方法是否比其他方法更可取。

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