On the analysis of phylogenetically paired designs.
On the analysis of phylogenetically paired designs.
复制标题
DOI：
10.1002/ece3.1406
复制
发表时间：
2015-02
影响因子：
2.6
通讯作者：
Macpherson, J. Michael
中科院分区：
文献类型：
--
作者：
Funk, Jennifer L.;Rakovski, Cyril S.;Macpherson, J. Michael
随着遗传控制的实验设计在生态学中越来越普遍，需要对这些数据集进行标准化的统计处理。系统发育配对设计规避了对解决系统发育的需要，并已被用于比较物种组，特别是在入侵生物学和适应领域。尽管这种方法被广泛使用，但配对设计的统计分析尚未得到严格评价。我们提出了一个混合模型的方法，包括对和物种的随机效应。这些随机效应引入了一个“双层”复合对称方差结构，该结构既捕获了对一对内相关物种的观测之间的相关性，也捕获了物种内重复测量之间的相关性。我们进行了一项模拟研究，以评估模型误设定对I型和II型错误率的影响。我们还提供了一个说明性的例子，数据包含分类相似的物种和几个结果变量的利益。我们发现，通过优化I型错误率和功效，将物种和配对作为随机效应的混合模型在这些遗传学显式模拟中的表现优于两种常用的参考模型（无或单一随机效应）。建议的混合模型产生可接受的I型和II型错误率，尽管没有系统发育树。这种设计可以推广到各种数据集，以分析相关受试者/物种集群中的重复测量。
As phylogenetically controlled experimental designs become increasingly common in ecology, the need arises for a standardized statistical treatment of these datasets. Phylogenetically paired designs circumvent the need for resolved phylogenies and have been used to compare species groups, particularly in the areas of invasion biology and adaptation. Despite the widespread use of this approach, the statistical analysis of paired designs has not been critically evaluated. We propose a mixed model approach that includes random effects for pair and species. These random effects introduce a “two-layer” compound symmetry variance structure that captures both the correlations between observations on related species within a pair as well as the correlations between the repeated measurements within species. We conducted a simulation study to assess the effect of model misspecification on Type I and II error rates. We also provide an illustrative example with data containing taxonomically similar species and several outcome variables of interest. We found that a mixed model with species and pair as random effects performed better in these phylogenetically explicit simulations than two commonly used reference models (no or single random effect) by optimizing Type I error rates and power. The proposed mixed model produces acceptable Type I and II error rates despite the absence of a phylogenetic tree. This design can be generalized to a variety of datasets to analyze repeated measurements in clusters of related subjects/species.
登录
查看更多内容
影响因子：
5.5
作者：
Funk, Jennifer L.
通讯作者：
Funk, Jennifer L.
影响因子：
3.3
作者：
Ackerly, DD
通讯作者：
Ackerly, DD
影响因子：
64.8
作者：
Funk, Jennifer L.;Vitousek, Peter M.
通讯作者：
Vitousek, Peter M.
影响因子：
2
作者：
Maddison, WP
通讯作者：
Maddison, WP
影响因子：
5.2
作者：
Kempel, Anne;Nater, Patrick;van Kleunen, Mark
通讯作者：
van Kleunen, Mark