Meta分析应用中应注意的几个关键问题

doi:10.17520/biods.2025308

生物多样性 ›› 2026, Vol. 34 ›› Issue (1): 25308. DOI: 10.17520/biods.2025308 cstr: 32101.14.biods.2025308

• 生态学数据分析方法专题 • 上一篇下一篇

Meta分析应用中应注意的几个关键问题

张霜¹(), 宋波²^,^*()()

1.中国科学院生态环境研究中心区域与城市生态安全全国重点实验室, 北京 100085
2.中国科学院昆明植物研究所云南省极小种群野生植物综合保护重点实验室, 昆明 650201

收稿日期:2025-08-05 接受日期:2025-12-10 出版日期:2026-01-20 发布日期:2026-01-21
通讯作者: 宋波
基金资助:
国家自然科学基金(31971481);国家自然科学基金(32371702);中国科学院西部之光交叉团队项目(xbzg-zdsys-202319)

Several key questions when conducting a meta-analysis

Shuang Zhang¹(), Bo Song²^,^*()()

1 State Key Laboratory of Regional and Urban Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
2 Yunnan Key Laboratory for Integrative Conservation of Plant Species with Extremely Small Populations, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China

Received:2025-08-05 Accepted:2025-12-10 Online:2026-01-20 Published:2026-01-21
Contact: Bo Song
Supported by:
National Natural Science Foundation of China(31971481);National Natural Science Foundation of China(32371702);CAS ‘Light of West China’ Program(xbzg-zdsys-202319)

摘要/Abstract

摘要：

Meta分析是通过对不同案例数据进行加权整合分析, 以得到普适性结论的重要统计工具, 在生态学领域具有广阔的应用价值。但长期以来, 科研人员对Meta分析的基本理念和方法体系具有较多的认识误区, 一定程度上造成了该方法的误用甚至错用。本文从Meta分析的操作步骤出发, 从其基本特征、文献的查询与筛选、效应值的构建、模型的选取、特殊数据结构的纳入、解释变量的引入、结果可靠性的判定、软件工具介绍等几个方面, 介绍了Meta分析的基本理念和应用中应注意的问题。相关概念和技术要点的厘清, 将为我们构建更为精准、合理的Meta分析模型, 提升结果可靠性提供帮助。Meta分析技术的不断更新进步, 必将为生态学领域众多基础科学问题的回答提供更有力、可靠的技术支撑。

关键词: 效应值, 异质性, 随机效应模型, 层次模型, Meta回归, 发表偏倚性

Abstract

Background & Aims: Meta-analysis is a crucial statistical tool for deriving generalized conclusions through the weighted analysis of data from case studies, with broad applications in ecology. However, for a long time, researchers have significant misconceptions regarding the fundamental principles and methodological framework of meta-analysis, which has contributed to its misuse, even erroneous application.

Review Results: According to the standard steps of conducting a meta-analysis, this article summarizes the basic feature of meta-analysis and highlights critical considerations for its application, encompassing aspects such as: defining key concepts, literature search and screening, construction of effect sizes, selection of models, incorporation of special data structures, inclusion of explanatory variables, assessment of result reliability, and relevant software tools.

Conclusion: The clarifications of related concepts and key points will aid in constructing more precise and appropriate meta-analysis models, thereby enhancing the reliability of results. Furthermore, continued advancements in meta-analysis methodology is poised to offer more robust and reliable technical approaches for addressing numerous fundamental scientific questions in ecology.

Key words: effect size, heterogeneity, random effects model, hierarchical model, meta-regression, publication bias

张霜, 宋波 (2026) Meta分析应用中应注意的几个关键问题. 生物多样性, 34, 25308. DOI: 10.17520/biods.2025308.

Shuang Zhang, Bo Song (2026) Several key questions when conducting a meta-analysis. Biodiversity Science, 34, 25308. DOI: 10.17520/biods.2025308.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2025308

https://www.biodiversity-science.net/CN/Y2026/V34/I1/25308

图/表 2

图1 PRISMA-文献筛选流程示意图。其中k1-k13代表每一步中涉及的文献数量, n为从文献中总共提取的效应值(即研究案例)数量。

Fig. 1 The PRISMA-flowchart in literature search. k1 to k13 represents the number of publications included or excluded at each stage of the literature search and n represents the total number of effect sizes derived from the selected literature.

图2 Meta分析的数据分析流程示意图。其中右侧方框部分为数据存在标准差缺失或特殊数据结构时的应对方法。虚线表示侦测到明显的发表偏倚性时, 应对累计效应值进行必要的修正。

Fig. 2 The flowchart of the data analysis in meta-analysis. The right part shows methods that can be used in datasets with missing SDs or different non-independent data structures. The dotted line represents the needed correction for cumulative effect size when publication bias was detected.

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Meta分析应用中应注意的几个关键问题

Several key questions when conducting a meta-analysis

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