生态和进化研究的大规模硅学复制

IF 13.9 1区生物学 Q1 ECOLOGY

Nature ecology & evolution Pub Date : 2024-09-26 DOI:10.1038/s41559-024-02530-5

Yefeng Yang, Erik van Zwet, Nikolaos Ignatiadis, Shinichi Nakagawa

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引用次数: 0

摘要

尽管人们越来越关注生态和进化研究的可复制性，但目前还没有一个全领域复制项目的结果。我们利用最先进的统计方法，开展了大规模的硅学复制项目。在没有选择性报告的情况下，具有边际统计意义的研究的可复制性为 30%-40%，而针对零假设 H0 提出 "强有力 "证据的研究的可复制性为 70%。前者需要大七倍的样本量才能达到后者的可复制性。我们呼吁改变研究的规划、开展和出版方式，建立透明、可信和可复制的生态学与进化论。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

A large-scale in silico replication of ecological and evolutionary studies

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A large-scale in silico replication of ecological and evolutionary studies

Despite the growing concerns about the replicability of ecological and evolutionary studies, no results exist from a field-wide replication project. We conduct a large-scale in silico replication project, leveraging cutting-edge statistical methodologies. Replicability is 30%–40% for studies with marginal statistical significance in the absence of selective reporting, whereas the replicability of studies presenting ‘strong’ evidence against the null hypothesis H₀ is >70%. The former requires a sevenfold larger sample size to reach the latter’s replicability. We call for a change in planning, conducting and publishing research towards a transparent, credible and replicable ecology and evolution.

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来源期刊

Nature ecology & evolution Agricultural and Biological Sciences-Ecology, Evolution, Behavior and Systematics

CiteScore

22.20

自引率

2.40%

发文量

282

期刊介绍： Nature Ecology & Evolution is interested in the full spectrum of ecological and evolutionary biology, encompassing approaches at the molecular, organismal, population, community and ecosystem levels, as well as relevant parts of the social sciences. Nature Ecology & Evolution provides a place where all researchers and policymakers interested in all aspects of life's diversity can come together to learn about the most accomplished and significant advances in the field and to discuss topical issues. An online-only monthly journal, our broad scope ensures that the research published reaches the widest possible audience of scientists.