社会科学研究的元分析:实践者指南

IF 5.9 2区 经济学 Q1 ECONOMICS
Zuzana Irsova, Hristos Doucouliagos, Tomas Havranek, T. D. Stanley
{"title":"社会科学研究的元分析:实践者指南","authors":"Zuzana Irsova, Hristos Doucouliagos, Tomas Havranek, T. D. Stanley","doi":"10.1111/joes.12595","DOIUrl":null,"url":null,"abstract":"This article provides concise, nontechnical, step-by-step guidelines on how to conduct a modern meta-analysis, especially in social sciences. We treat publication bias, <i>p-</i>hacking, and systematic heterogeneity as phenomena meta-analysts must always confront. To this end, we provide concrete methodological recommendations. Meta-analysis methods have advanced notably over the last few years. Yet many meta-analyses still rely on outdated approaches, some ignoring publication bias and systematic heterogeneity. While limitations persist, recently developed techniques allow robust inference even in the face of formidable problems in the underlying empirical literature. The purpose of this paper is to summarize the state of the art in a way accessible to aspiring meta-analysts in any field. We also discuss how meta-analysts can use advances in artificial intelligence to work more efficiently.","PeriodicalId":51374,"journal":{"name":"Journal of Economic Surveys","volume":null,"pages":null},"PeriodicalIF":5.9000,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Meta-analysis of social science research: A practitioner's guide\",\"authors\":\"Zuzana Irsova, Hristos Doucouliagos, Tomas Havranek, T. D. Stanley\",\"doi\":\"10.1111/joes.12595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article provides concise, nontechnical, step-by-step guidelines on how to conduct a modern meta-analysis, especially in social sciences. We treat publication bias, <i>p-</i>hacking, and systematic heterogeneity as phenomena meta-analysts must always confront. To this end, we provide concrete methodological recommendations. Meta-analysis methods have advanced notably over the last few years. Yet many meta-analyses still rely on outdated approaches, some ignoring publication bias and systematic heterogeneity. While limitations persist, recently developed techniques allow robust inference even in the face of formidable problems in the underlying empirical literature. The purpose of this paper is to summarize the state of the art in a way accessible to aspiring meta-analysts in any field. We also discuss how meta-analysts can use advances in artificial intelligence to work more efficiently.\",\"PeriodicalId\":51374,\"journal\":{\"name\":\"Journal of Economic Surveys\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2023-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Economic Surveys\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://doi.org/10.1111/joes.12595\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Economic Surveys","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1111/joes.12595","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 1

摘要

这篇文章提供了简明的,非技术的,逐步指导如何进行现代元分析,特别是在社会科学。我们将发表偏倚、p-hacking和系统异质性视为元分析必须面对的现象。为此,我们提出具体的方法建议。元分析方法在过去几年中取得了显著进展。然而,许多元分析仍然依赖于过时的方法,有些忽略了发表偏倚和系统异质性。虽然局限性仍然存在,但最近开发的技术即使在面对潜在经验文献中的可怕问题时也可以进行稳健的推断。本文的目的是以一种对任何领域有抱负的元分析人员都可以访问的方式总结当前的艺术状态。我们还讨论了元分析师如何利用人工智能的进步来提高工作效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Meta-analysis of social science research: A practitioner's guide
This article provides concise, nontechnical, step-by-step guidelines on how to conduct a modern meta-analysis, especially in social sciences. We treat publication bias, p-hacking, and systematic heterogeneity as phenomena meta-analysts must always confront. To this end, we provide concrete methodological recommendations. Meta-analysis methods have advanced notably over the last few years. Yet many meta-analyses still rely on outdated approaches, some ignoring publication bias and systematic heterogeneity. While limitations persist, recently developed techniques allow robust inference even in the face of formidable problems in the underlying empirical literature. The purpose of this paper is to summarize the state of the art in a way accessible to aspiring meta-analysts in any field. We also discuss how meta-analysts can use advances in artificial intelligence to work more efficiently.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
11.30
自引率
3.80%
发文量
57
期刊介绍: As economics becomes increasingly specialized, communication amongst economists becomes even more important. The Journal of Economic Surveys seeks to improve the communication of new ideas. It provides a means by which economists can keep abreast of recent developments beyond their immediate specialization. Areas covered include: - economics - econometrics - economic history - business economics
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信