An effect size for comparing the strength of morphological integration across studies.
An effect size for comparing the strength of morphological integration across studies.
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DOI：
10.1111/evo.14595
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发表时间：
2022-10
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影响因子：
--
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--
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了解表型性状如何以及为什么协同变化是进化生物学的主要兴趣。生物学家长期以来一直试图描述生物形态整合的程度，但由于缺乏可靠的总结测量和测试程序，比较不同分类群的一组特征的整合水平一直受到阻碍。在这里，我们为此提出了一个标准化的效应大小，从相对特征值方差计算，。首先，我们评估了不同条件下的几个特征值色散指数，并表明仅在样本大小和变量数量上保持稳定。然后我们证明，只要从计算中排除冗余维度，就可以准确地表征协变的输入模式。然而，我们也表明抽样分布的方差取决于性状共变的输入水平，因此不适合直接比较。作为解决方案，我们建议转换为标准化效应大小（Z - score）来表示一组特征的整合程度。我们还提出了一个双样本检验来比较分类群之间的整合强度，并表明该检验具有适当的统计性质。我们提供了实现该过程的软件，并举例说明了它的使用。
Understanding how and why phenotypic traits covary is a major interest in evolutionary biology. Biologists have long sought to characterize the extent of morphological integration in organisms, but comparing levels of integration for a set of traits across taxa has been hampered by the lack of a reliable summary measure and testing procedure. Here, we propose a standardized effect size for this purpose, calculated from the relative eigenvalue variance, . First, we evaluate several eigenvalue dispersion indices under various conditions, and show that only remains stable across samples size and the number of variables. We then demonstrate that accurately characterizes input patterns of covariation, so long as redundant dimensions are excluded from the calculations. However, we also show that the variance of the sampling distribution of depends on input levels of trait covariation, making unsuitable for direct comparisons. As a solution, we propose transforming to a standardized effect size (Z‐score) for representing the magnitude of integration for a set of traits. We also propose a two‐sample test for comparing the strength of integration between taxa, and show that this test displays appropriate statistical properties. We provide software for implementing the procedure, and an empirical example illustrates its use.
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影响因子：
--
作者：
Adams, DC;Rohlf, FJ;Slice, DE
通讯作者：
Slice, DE
影响因子：
3.2
作者：
Bookstein, FL;Gunz, P;Seidler, H
通讯作者：
Seidler, H
影响因子：
3.3
作者：
CHEVERUD, JM
通讯作者：
CHEVERUD, JM
影响因子：
6.5
作者：
Adams, Dean C.
通讯作者：
Adams, Dean C.
影响因子：
6.6
作者：
Baken, Erica K.;Collyer, Michael L.;Adams, Dean C.
通讯作者：
Adams, Dean C.