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Identification of and correction for publication bias

Maximilian Kasy () and Isaiah Andrews

No 49yst, MetaArXiv from Center for Open Science

Abstract: 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.

New Economics Papers: this item is included in nep-sog
Date: 2018-11-28
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https://osf.io/download/5bfec3c135444800196313d7/

Related works:
Journal Article: Identification of and Correction for Publication Bias (2019) Downloads
Working Paper: Identification of and correction for publication bias (2017) Downloads
Working Paper: Identification of and Correction for Publication Bias (2017) Downloads
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Persistent link: https://EconPapers.repec.org/RePEc:osf:metaar:49yst

DOI: 10.31219/osf.io/49yst

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