Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/286354 
Erscheinungsjahr: 
2023
Schriftenreihe/Nr.: 
IES Working Paper No. 25/2023
Verlag: 
Charles University in Prague, Institute of Economic Studies (IES), Prague
Zusammenfassung: 
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 Yet many meta-analyses still rely on outdated approaches, some ignoring publication bias and systematic heterogeneity.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.
Schlagwörter: 
meta-analysis
publication bias
p-hacking
artificial intelligence
model uncertainty
JEL: 
A14
B49
C83
Dokumentart: 
Working Paper

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