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Meta-Regression Methods for Detecting and Estimating Empirical Effects in the Presence of Publication Selection

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  • T. D. Stanley

Abstract

This study investigates the small-sample performance of meta-regression methods for detecting and estimating genuine empirical effects in research literatures tainted by publication selection. Publication selection exists when editors, reviewers or researchers have a preference for statistically significant results. Meta-regression methods are found to be robust against publication selection. Even if a literature is dominated by large and unknown misspecification biases, precision-effect testing and joint precision-effect and meta-significance testing can provide viable strategies for detecting genuine empirical effects. Publication biases are greatly reduced by combining two biased estimates, the estimated meta-regression coefficient on precision (1/"Se") and the unadjusted-average effect. Copyright 2008 Blackwell Publishing Ltd and the Department of Economics, University of Oxford.

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Bibliographic Info

Article provided by Department of Economics, University of Oxford in its journal Oxford Bulletin of Economics and Statistics.

Volume (Year): 70 (2008)
Issue (Month): 1 (02)
Pages: 103-127

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Handle: RePEc:bla:obuest:v:70:y:2008:i:1:p:103-127

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  12. Gorg, Holger & Strobl, Eric, 2001. "Multinational Companies and Productivity Spillovers: A Meta-analysis," Economic Journal, Royal Economic Society, vol. 111(475), pages F723-39, November.
  13. T. D. Stanley, 2005. "Beyond Publication Bias," Journal of Economic Surveys, Wiley Blackwell, vol. 19(3), pages 309-345, 07.
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