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Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (11): 1-12    DOI: 10.11925/infotech.2096-3467.2021.0515
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Review of Application and Evolution of Meta-Analysis in Social Sciences
Li Xiao1,2,Qu Jiansheng2,3()
1Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2University of Chinese Academy of Sciences, Beijing 100049, China
3Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu 610041, China
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[Objective] This paper reviews the latest application and evolution of meta-analysis in social sciences. [Methods] First, we summarized the main characteristics of meta-analysis as well as the key problems facing the application of meta-analysis in social sciences. Then, we conducted case studies with the MetaBUS and CoDa databases. Finally, we exmined the meta-analysis from different perspectives. [Results] The meta-analysis in social sciences mainly studied the aggregated data meta with traditional methods, such as standardized mean differences and correlation coefficients. At present, the key issues are effect size deviation, lack of transparency and quality assessment, as well as time and manpower consuming, etc. Meta-analytics database and meta-analytic research can benefit each other. Data repository, open science movement and artificial intelligence technology all posed various significant impacts on meta-analytical research. [Limitations] The content analysis is mainly based on sampling samples, so there are potential limitations in comprehensively revealing the characteristics and problems of meta-analysis. [Conclusions] There are still many problems to be addressed for meta-analysis in social sciences, and all parties need to work together to improve these research and draw better conclusions.

Key wordsMeta-Analysis      Social Science      Main Features      Key Problems      Meta-Analysis Database     
Received: 24 May 2021      Published: 23 December 2021
ZTFLH:  G350  
Fund:National Key Research and Development Project of China(2018YFC1509007)
Corresponding Authors: Qu Jiansheng,ORCID:0000-0002-2806-3447     E-mail:

Cite this article:

Li Xiao, Qu Jiansheng. Review of Application and Evolution of Meta-Analysis in Social Sciences. Data Analysis and Knowledge Discovery, 2021, 5(11): 1-12.

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Top 10 Disciplines Based on Meta-Analysis of WoS in Social Science
Number of Meta-Analysis by Year in Social Science
名称 作者或机构 适用学科 主要贡献
PRISMA声明(系统评价和元分析的首选报告)[10] PRISMA小组(2009) 最初专注于医学领域随机试验,后来被各个领域广泛采用 提供了系统评价或元分析报告要包括的27个项目清单以及描述文献检索过程及结果的流程图
MARS (元分析报告标准)[11] 美国心理协会
(APA 2008,2010)
心理学相关学科以及其他社会科学学科 所提供的元分析研究报告格式包括标题、摘要、引言、方法、结果、讨论,方法部分包括样本纳入与排除标准、调节变量和中介变量分析、检索方式、编码程序、统计方法
Campbell协作网系统评价方法[12] Campbell协作网方法小组 犯罪与司法、教育、国际发展以及社会福利等领域 为Campbell协作网干预效果系统评价的实施提供了详细的方法指南。其所列大部分方法指南适用于所有综述主题,但有些可能并不完全适用于非干预综述
Standards or Guidelines Used for Meta-analysis in Social Science
Data Extraction by Two Types of Meta-Analysis
Manual Literature Screening Process
级别 元数据
文献级别信息 期刊名称、卷号、发行号、起始页和结束页、出版年份,以及财政支持情况(如拨款资助:是或否)
变量级别信息 报告的变量名、样本量、确切的样本量、分类节点、分类节点名、概念反转、变量均值、标准差、可靠性值、可靠性值是否为系数α(是/否)、时间点、回复率、样本编号、数据来源和数据对象、分析单位、国家、编码置信度
Main Data for MetaBUS Database
One Annotated Instance in CoDa’s Model
Some Meta-Analysis Extracting Data from Data Repositories
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