Collaborative research: ABI Development: Making Advanced Statistical Tools Accessible for Quantitative Research Synthesis and Discovery in Ecology and Evolutionary Biology

该奖项旨在建立一个易于使用的程序，用于在生态和进化领域（E&amp；E）中开展和教授元分析，通过调整和发展现有的医学元分析程序来满足这些领域科学界的独特需求。荟萃分析是独立研究的定量综合。就像在医学和社会科学领域一样，它已经成为总结研究成果和概括研究结果的重要方法。有一个迫切需要新的统计软件的荟萃分析在机电采用当前的，前沿的方法。使这些统计工具广泛可用，极有可能推动新的科学进步和见解，就像E&amp；E中的第一代元分析软件一样。这个名为OpenMeta for Ecology and Evolution （OpenMEE）的新软件将是一个开源和跨平台的程序，将促进适用于生态和进化数据元分析的统计方法的实施，并将包括一个专门为这些领域的独特挑战和研究综合惯例设计的用户界面。然后，直观的图形用户界面（GUI）将与用流行的开源统计编程语言r编写的分析例程无缝集成。因此，新手用户将能够利用这些例程来执行复杂的元分析，而无需了解高级编程。此外，OpenMEE的设计使那些有能力的程序员的用户能够以一种直接的方式结合新的统计发展，从而允许用户社区无限地开发和更新OpenMEE。OpenMEE将介绍E&amp；E中用于元分析的前沿统计发展，包括复杂的元回归模型和系统发育分析。将更强大的定量研究综合工具交到机电科学家手中，将对这些领域的研究进展产生巨大影响。从事该项目的科学家们在成功指导高中生、本科生、研究生和博士后（包括那些属于代表性不足群体的人）方面有着坚实的记录，并将继续积极地招募和培训所有这些级别的人员。OpenMEE将在讲习班和短期课程中以及以电子方式传播。在招募这些课程的参与者时，研究人员将努力从代表性不足的群体以及其他群体中识别和吸引研究生和博士后研究人员；他们将能够安排课程的费用，以便能够为缺乏支持的学生提供旅行奖学金。最后，未被充分代表的少数民族学生和其他人将通过国家自然科学基金&amp；#8208；资助的石溪大学科学与数学教育中心，并从南佛罗里达大学资源丰富、代表性不足的学生群体中招募学生。关于这个项目的更多信息可以在http://www.cebm.brown.edu/OpenMEE上找到。

An award is made to build an easy-to-use program for carrying out and teaching meta-analysis in in the fields of ecology and evolution (E&E), by adapting and developing an existing medical meta-analysis program for the unique needs of the scientific community in these fields. Meta-analysis is the quantitative synthesis of independent studies. It has become an important approach for summarizing research results and generalizing from their findings in E&E, as it has in medicine and the social sciences. There is a compelling need for new statistical software for meta-analysis in E&E employing current, cutting edge methodology. Making these statistical tools widely available is highly likely to propel new scientific advances and insights, as did the first generation of meta-analysis software in E&E. This new software, called OpenMeta for Ecology and Evolution (OpenMEE), will be open-source and cross-platform program, will facilitate implementation of statistical methods appropriate for meta-analysis of ecological and evolutionary data, and will include a user interface specifically designed for the unique challenges and conventions of research synthesis in these fields. Then intuitive graphical user interface (GUI) will seamlessly integrate with analytic routines written in the popular open-source statistical programming language R. Novice users will thus be able to take advantage of such routines to carry out sophisticated meta-analyses without needing to know advanced programming. Furthermore, OpenMEE is designed so that those users who are competent programmers can incorporate new statistical developments in a straightforward manner, allowing OpenMEE to be developed and updated indefinitely by the user community. OpenMEE will be introduced with cutting edge statistical developments for meta-analysis in E&E, including complex meta-regression models and phylogenetic analyses. Putting much more powerful tools for quantitative research synthesis into the hands of scientists in E&E will have dramatic effects on research progress in these fields.The scientists working on this project have a solid record of successfully mentoring high school students, undergraduates, graduate students, and postdoctoral fellows, including those belonging to underrepresented groups, and will continue to work actively to recruit and train people at all of these levels. OpenMEE will be disseminated in workshops and short courses, as well as electronically. In recruiting participants for these courses, the researchers will work to identify and attract graduate students and postdoctoral researchers from underrepresented groups as well as others; they will be able to structure the fees for the courses so as to be able to offer travel fellowships for students lacking support to attend the courses. Finally, underrepresented minority students and others will be recruited for research experience through the NSF‐funded Center for Science and Mathematics Education at Stony Brook University, and by recruiting from the rich resource of the high underrepresented student population at University of South Florida. More information about this project may be found at: http://www.cebm.brown.edu/OpenMEE.