Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/98446
Authors: 
Bruns, Stephan B.
Year of Publication: 
2013
Series/Report no.: 
Jena Economic Research Papers 2013-040
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 empirical 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 proposed systematically outperform the prior gold standard of meta-regression analysis of regression 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.
Subjects: 
data mining
meta-analysis
meta-regression
Monte Carlo simulation
publication bias
JEL: 
C12
C15
C40
Document Type: 
Working Paper

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