那么,它比其他东西更好吗?用随机效应荟萃分析的结果来描述效应大小的百分位数。

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Peter Boedeker,Gena Nelson,Hannah Carter
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引用次数: 0

摘要

对效应大小的描述最好参照文献中的效应大小。随机效应荟萃分析是对文献中的相关效应进行系统综合,从而得出人群中效应分布的估计值。我们建议使用随机效应荟萃分析的估计均值和方差来描述观察到的效应大小。观察到的效应大小在估计的群体效应分布中的百分位数可以描述观察到的效应大小。由于群体估计值存在不确定性,我们建议在描述效应大小时使用预测分布(常用于估计荟萃分析中的预测区间)作为参考分布。这样,就可以计算出预测分布内观察效应的百分位数和效应大小 95% 置信区间的界限。目前有大量的荟萃分析,包括各种结果和背景,因此所介绍的方法对许多研究人员和从业人员都很有用。我们演示了如何应用易于使用的 Excel 工作表来自动计算这些百分位数。随后,我们进行了一项模拟研究,对该方法在一系列条件下的性能进行了评估。我们还为元分析师和进行单项研究的研究人员提供了建议(和注意事项)。(PsycInfo 数据库记录 (c) 2024 APA,保留所有权利)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
So is it better than something else? Using the results of a random-effects meta-analysis to characterize the magnitude of an effect size as a percentile.
The characterization of an effect size is best made in reference to effect sizes found in the literature. A random-effects meta-analysis is the systematic synthesis of related effects from across a literature, producing an estimate of the distribution of effects in the population. We propose using the estimated mean and variance from a random-effects meta-analysis to inform the characterization of an observed effect size. The percentile of an observed effect size within the estimated distribution of population effects can describe the magnitude of the observed effect. Because there is uncertainty in the population estimates, we propose using the prediction distribution (used frequently to estimate the prediction interval in a meta-analysis) to serve as the reference distribution when characterizing an effect size. Doing so, the percentile of an observed effect and the limits of the effect size's 95% confidence interval within the prediction distribution are calculated. With numerous meta-analyses available including various outcomes and contexts, the presented method can be useful to many researchers and practitioners. We demonstrate the application of an easy-to-use Excel worksheet to automate these percentile calculations. We follow this with a simulation study evaluating the method's performance over a range of conditions. Recommendations (and cautions) for meta-analysts and researchers conducting a single study are provided. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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来源期刊
Psychological methods
Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
13.10
自引率
7.10%
发文量
159
期刊介绍: Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.
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