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Beyond Publication Bias

T. D. Stanley

出版	SSRN, 2005
URL	http://books.google.com.hk/books?id=ow_jzwEACAAJ&hl=&source=gbs_api

註釋

This review considers several meta-regression and graphical methods that can differentiate genuine empirical effect from publication bias. Publication selection exists when editors, reviewers, or researchers have a preference for statistically significant results. Because all areas of empirical research are susceptible to publication selection, any average or tally of significant/insignificant studies is likely to be biased and potentially misleading. Meta-regression analysis can see through the murk of random sampling error and selected misspecification bias to identify the underlying statistical structures that characterize genuine empirical effect. Meta-significance testing and precision-effect testing (PET) are offered as a means to identify empirical effect beyond publication bias and are applied to four areas of empirical economics research - minimum wage effects, union-productivity effects, price elasticities, and tests of the natural rate hypothesis.