Methods for estimating the sampling variance of the standardized mean difference.

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Manuel Suero, Juan Botella, Juan I Durán
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引用次数: 4

Abstract

One of the most widely used effect size indices for meta-analysis in psychology is the standardized mean difference (SMD). The most common way to synthesize a set of estimates of the SMD is to weight them by the inverse of their variances. For this, it is necessary to estimate the corresponding sampling variances. Meta-analysts have a formula for obtaining unbiased estimates of sampling variances, but they often use a variety of alternative, simpler methods. The bias and efficiency of five different methods that have been proposed and that are implemented in different computerized calculation tools are compared and assessed. The data from a set of published meta-analyses are also reanalyzed, calculating the combined estimates and their confidence intervals, as well as estimates of the specific, between-studies variance, using the five estimation methods. This test of sensitivity shows that the results of a meta-analysis can change noticeably depending on the method used to estimate the sampling variance of SMD values, especially under a random-effects model. Some practical recommendations are made about how to choose and implement the methods in calculation resources. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

估计标准化平均差抽样方差的方法。
标准化平均差(SMD)是心理学荟萃分析中应用最广泛的效应大小指标之一。合成一组SMD估计的最常见方法是通过方差的倒数来对它们进行加权。为此,有必要估计相应的抽样方差。元分析者有一个公式来获得抽样方差的无偏估计,但他们经常使用各种替代的、更简单的方法。本文比较和评估了在不同计算机计算工具中提出和实施的五种不同方法的偏倚和效率。我们还重新分析了一组已发表的荟萃分析的数据,计算了综合估计值及其置信区间,以及使用五种估计方法对具体研究间方差的估计。这一敏感性检验表明,元分析的结果可能会因估计SMD值的抽样方差的方法而发生显著变化,特别是在随机效应模型下。对计算资源中方法的选择和实现提出了一些实用的建议。(PsycInfo数据库记录(c) 2023 APA,版权所有)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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