Identification of and correction for publication bias
Maximilian Kasy () and
No 49yst, MetaArXiv from Center for Open Science
Some empirical results are more likely to be published than others. Selective publication leads to biased estimates and distorted inference. We propose two approaches for identifying the conditional probability of publication as a function of a study’s results, the first based on systematic replication studies and the second on meta-studies. For known conditional publication probabilities, we propose bias-corrected estimators and confidence sets. We apply our methods to recent replication studies in experimental economics and psychology, and to a meta-study on the effect of the minimum wage. When replication and meta-study data are available, we find similar results from both.
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Journal Article: Identification of and Correction for Publication Bias (2019)
Working Paper: Identification of and correction for publication bias (2017)
Working Paper: Identification of and Correction for Publication Bias (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:osf:metaar:49yst
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