菱形比:meta分析中显示异质性程度的直观指标

IF 1.5 3区 心理学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS British Journal of Mathematical & Statistical Psychology Pub Date : 2021-11-02 DOI:10.1111/bmsp.12258
Maxwell Cairns, Geoff Cumming, Robert Calin-Jageman, Luke A. Prendergast
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引用次数: 3

摘要

meta分析的结果通常在森林图中描绘为菱形,其长度为兴趣汇总度量的95%置信区间(CI)。钻石比率(DR)是随机效应元分析得出的钻石长度与固定效应元分析得出的钻石长度之比。DR是一个简单的视觉指标,表明从固定效应到随机效应元分析所引起的变化量。DR大于1.0的值越大,表明相对于效应方差的异质性越大。我们研究了DR的性质,以及它与四种常规但更复杂的异质性测量的关系。我们首次在DR上提出了一个CI,并表明它在覆盖方面表现良好。我们提供了计算DR及其CI的示例代码,并在森林图中显示它们。我们得出结论,DR是一个有用的指标,可以帮助学生和研究人员了解异质性,并在特定情况下评估其程度。
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The diamond ratio: A visual indicator of the extent of heterogeneity in meta-analysis

The result of a meta-analysis is conventionally pictured in the forest plot as a diamond, whose length is the 95% confidence interval (CI) for the summary measure of interest. The Diamond Ratio (DR) is the ratio of the length of the diamond given by a random effects meta-analysis to that given by a fixed effect meta-analysis. The DR is a simple visual indicator of the amount of change caused by moving from a fixed-effect to a random-effects meta-analysis. Increasing values of DR greater than 1.0 indicate increasing heterogeneity relative to the effect variances. We investigate the properties of the DR, and its relationship to four conventional but more complex measures of heterogeneity. We propose for the first time a CI on the DR, and show that it performs well in terms of coverage. We provide example code to calculate the DR and its CI, and to show these in a forest plot. We conclude that the DR is a useful indicator that can assist students and researchers to understand heterogeneity, and to appreciate its extent in particular cases.

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来源期刊
CiteScore
5.00
自引率
3.80%
发文量
34
审稿时长
>12 weeks
期刊介绍: The British Journal of Mathematical and Statistical Psychology publishes articles relating to areas of psychology which have a greater mathematical or statistical aspect of their argument than is usually acceptable to other journals including: • mathematical psychology • statistics • psychometrics • decision making • psychophysics • classification • relevant areas of mathematics, computing and computer software These include articles that address substantitive psychological issues or that develop and extend techniques useful to psychologists. New models for psychological processes, new approaches to existing data, critiques of existing models and improved algorithms for estimating the parameters of a model are examples of articles which may be favoured.
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