Statistical Methods for Comparative Analyses

常规的统计方法不能用来研究物种之间的变异或相关性，因为由于它们共同的进化历史，预期的相似性模式违反了观测独立性的基本假设。该项目涉及开发和评估可用于考虑这一依赖关系的特殊统计方法。提出了广义最小二乘模型、混合效应模型、广义线性模型(使用对非独立数据的扩展)和多变量数据(特别是从几何形态测量研究获得的形状变量组)分析的广义工作。对网状进化模型和地理抽样模型的概括也将被研究。这些方法将被应用于几个数据集，以评估它们在实践中的有效性。该项目包括对研究生的支持，以及首席研究人员多年来向科学界提供的软件程序的增强。

0212023RohlfOrdinary statistical methods cannot be used to study variation or correlations among species because the fundamental assumption of independence of observations is violated due to the pattern of similarity expected as a result of their common evolutionary history. This project is concerned with the development and evaluation of special statistical methods that can be used to take this dependence into account. Work is proposed on generalized least-squares models, mixed effects models, generalized linear models (using extensions for non-independent data), and generalizations for the analysis of multivariate data (especially for suites of shape variables obtained from geometric morphometric studies). Generalizations to models of reticulated evolution and geographic sampling will also be investigated. These methods will be applied to several data sets in order to evaluate their usefulness in practice.Support for a graduate student is included in the project, along with enhancements to software programs that the Principal Investigator has made available for many years to the science community.