Meta-Analysis of Social Science Research: A Practitioner’s Guide

Zuzana Irsova, Chris Doucouliagos, Tomas Havranek and T. D. Stanley

EconStor Preprints from ZBW - Leibniz Information Centre for Economics

Abstract: This paper 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 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 Yet many meta-analyses still rely on outdated approaches, some ignoring publication bias and systematic heterogeneity.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.

Keywords: meta-analysis; publication bias; p-hacking; artificial intelligence; model uncertainty (search for similar items in EconPapers)
JEL-codes: A14 B49 C83 (search for similar items in EconPapers)
Date: 2023
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (2)

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https://www.econstor.eu/bitstream/10419/273719/1/guidelines.pdf (application/pdf)

Related works:
Journal Article: Meta‐analysis of social science research: A practitioner's guide (2024)
Working Paper: Meta-Analysis of Social Science Research: A Practitioner´s Guide (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:zbw:esprep:273719

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