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Identifying Genuine Effects in Observational Research by Means of Meta-Regressions

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  • Stephan B. Bruns

    ()
    (Max Planck Institute of Economics, Jena)

Abstract

Meta-regression models are increasingly utilized to integrate empirical results across studies while controlling for the potential threats of data-mining and publication bias. We propose extended meta-regression models and evaluate their performance in identifying genuine em- pirical effects by means of a comprehensive simulation study for various scenarios that are prevalent in empirical economics. We can show that the meta-regression models here pro- posed systematically outperform the prior gold standard of meta-regression analysis of re- gression coefficients. Most meta-regression models are robust to the presence of publication bias, but data-mining bias leads to seriously inflated type I errors and has to be addressed explicitly.

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Bibliographic Info

Paper provided by Friedrich-Schiller-University Jena, Max-Planck-Institute of Economics in its series Jena Economic Research Papers with number 2013-040.

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Date of creation: 27 Sep 2013
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Handle: RePEc:jrp:jrpwrp:2013-040

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Keywords: Meta-regression; meta-analysis; publication bias; data mining; Monte Carlo simulatio;

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