{"title":"Durga:用于效应大小估计和可视化的 R 软件包。","authors":"Md Kawsar Khan, Donald James McLean","doi":"10.1093/jeb/voae073","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":50198,"journal":{"name":"Journal of Evolutionary Biology","volume":" ","pages":"986-993"},"PeriodicalIF":2.1000,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Durga: an R package for effect size estimation and visualization.\",\"authors\":\"Md Kawsar Khan, Donald James McLean\",\"doi\":\"10.1093/jeb/voae073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":50198,\"journal\":{\"name\":\"Journal of Evolutionary Biology\",\"volume\":\" \",\"pages\":\"986-993\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2024-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Evolutionary Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/jeb/voae073\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Evolutionary Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/jeb/voae073","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ECOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
统计分析和数据可视化是科学传播不可或缺的组成部分。当前数据分析实践中的一个主要问题是过度依赖和滥用 p 值。研究人员一直倡导估算和报告定量研究的效应大小,以提高数据分析的清晰度和有效性。迄今为止,科学出版物中的效应大小报告主要局限于数字表格,尽管效应大小图是一种更有效的结果交流方式。我们开发了 Durga R 软件包,用于估计和绘制配对组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效应大小以及效应大小的引导置信区间。Durga 的核心功能是将效应大小可视化与传统绘图方法相结合。Durga 是一个功能强大、易于使用的统计和数据可视化软件包,可灵活地使用不同的统计方法估算配对和非配对数据的效应大小。Durga 提供了大量绘制效应大小的选项,允许用户以最翔实、最美观的方式绘制数据。在此,我们将介绍该软件包及其各种功能。我们将进一步介绍使用示例数据集估算和绘制效应大小的工作流程。
Durga: an R package for effect size estimation and visualization.
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.
期刊介绍:
It covers both micro- and macro-evolution of all types of organisms. The aim of the Journal is to integrate perspectives across molecular and microbial evolution, behaviour, genetics, ecology, life histories, development, palaeontology, systematics and morphology.