Statistical Methods for Comparative Analyses

比较分析的统计方法

• 批准号: 0212023
• 负责人: F. James Rohlf
• 金额: $ 10万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2005-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0212023&HistoricalAwards=false
• 关键词: Statistical; Methods; Comparative; Analyses

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.

0212023Rohlf普通的统计方法不能用来研究物种之间的变异或相关性，因为观察结果独立的基本假设被违反了，因为它们共同的进化历史导致了相似的模式。该项目涉及开发和评估可用于考虑这种依赖性的特殊统计方法。工作提出了广义最小二乘模型，混合效应模型，广义线性模型（使用非独立数据的扩展），和概括的多变量数据的分析（特别是对套房的形状变量从几何形态学研究）。 也将研究网状进化和地理抽样模型的推广。 这些方法将被应用到几个数据集，以评估其实用性在practices.Support研究生包括在该项目中，沿着增强软件程序，首席研究员已经提供了多年的科学界。