立场文件:在环境科学中更好地利用基于相关和回归的方法的常见错误和解决办法

IF 4.6 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Damien Tedoldi , Boram Kim , Santiago Sandoval , Nicolas Forquet , Bruno Tassin
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引用次数: 0

摘要

虽然经验建模在环境科学中仍然是一种流行的做法,但在最近的研究中遇到了大量滥用基于相关和回归的技术,尽管这些技术在课程和教科书中都有描述。本立场文件回顾了最常见的问题,并根据这些方法的基本假设,为理解这些方法的兴趣和局限性提供了理论背景。我们呼吁重新考虑误导的做法,包括:将线性回归应用于不显示线性模式的数据点、未能确定有影响的点、对经验关系进行不适当的外推、对“统计显著性”的高估、将属于不同群体的数据汇集在一起,以及最重要的是,没有数据可视化的计算。我们敦促审稿人对这些方面保持警惕。我们还回顾,存在其他办法来克服突出的缺点,从而有助于对结果作出更准确的解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Position paper: Common mistakes and solutions for a better use of correlation- and regression-based approaches in environmental sciences

Position paper: Common mistakes and solutions for a better use of correlation- and regression-based approaches in environmental sciences
While empirical modelling remains a popular practice in environmental sciences, an alarming number of misuses of correlation- and regression-based techniques are encountered in recent research, although these techniques are described in courses and textbooks. This position paper reviews the most common issues, and provides theoretical background for understanding the interests and limitations of these methods, based on their underlying assumptions. We call for a reconsideration of misleading practices, including: the application of linear regression to data points that do not display a linear pattern, the failure to pinpoint influential points, the inappropriate extrapolation of empirical relationships, the overrated search for “statistical significance”, the pooling of data belonging to different populations, and, most importantly, calculations without data visualization. We urge reviewers to be vigilant on these aspects. We also recall the existence of alternative approaches to overcome the highlighted shortcomings, and thus contribute to a more accurate interpretation of the results.
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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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