School of Natural Sciences, Macquarie University, Sydney, NSW, Australia.
Institute of Biology, Freie Universität Berlin, Berlin, Germany.
J Evol Biol. 2024 Aug 1;37(8):986-993. doi: 10.1093/jeb/voae073.
Statistical analysis and data visualization are integral parts of science communication. One of the major issues in current data analysis practice is an overdependency on-and misuse of-p-values. Researchers have been advocating for the estimation and reporting of effect sizes for quantitative research to enhance the clarity and effectiveness of data analysis. Reporting effect sizes in scientific publications has until now been mainly limited to numeric tables, even though effect size plotting is a more effective means of communicating results. We have developed the Durga R package for estimating and plotting effect sizes for paired and unpaired group comparisons. Durga allows users to estimate unstandardized and standardized effect sizes and bootstrapped confidence intervals of the effect sizes. The central functionality of Durga is to combine effect size visualizations with traditional plotting methods. Durga is a powerful statistical and data visualization package that is easy to use, providing the flexibility to estimate effect sizes of paired and unpaired data using different statistical methods. Durga provides a plethora of options for plotting effect size, which allows users to plot data in the most informative and aesthetic way. Here, we introduce the package and its various functions. We further describe a workflow for estimating and plotting effect sizes using example data sets.
统计分析和数据可视化是科学交流的重要组成部分。目前数据分析实践中的一个主要问题是过度依赖和误用 p 值。研究人员一直在提倡对定量研究进行效应量的估计和报告，以提高数据分析的清晰度和有效性。到目前为止，科学出版物中报告效应量主要局限于数字表格，尽管效应量绘图是一种更有效的结果交流方式。我们已经开发了 Durga R 包，用于估计和绘制配对和非配对组比较的效应量。Durga 允许用户估计非标准化和标准化的效应量以及效应量的自举置信区间。Durga 的核心功能是将效应量可视化与传统绘图方法相结合。Durga 是一个功能强大的统计和数据可视化包，易于使用，提供了使用不同统计方法估计配对和非配对数据的效应量的灵活性。Durga 提供了大量的效应量绘图选项，允许用户以最具信息量和美学的方式绘制数据。在这里，我们介绍了这个包及其各种功能。我们进一步描述了使用示例数据集估计和绘制效应量的工作流程。
