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Project Citation: 

Andrews, Isaiah, and Kasy, Maximilian. Replication data for: Identification of and Correction for Publication Bias. Nashville, TN: American Economic Association [publisher], 2019. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-12-07. https://doi.org/10.3886/E116208V1

Project Description

Summary:  View help for Summary 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.

Scope of Project

Subject Terms:  View help for Subject Terms Publication Bias; Replication; Meta-analysis
JEL Classification:  View help for JEL Classification
      C13 Estimation: General
      C90 Design of Experiments: General
      I23 Higher Education; Research Institutions
      J23 Labor Demand
      J38 Wages, Compensation, and Labor Costs: Public Policy
      L82 Entertainment; Media
Data Type(s):  View help for Data Type(s) observational data; program source code; experimental data

Methodology

Data Source:  View help for Data Source Data are drawn from eonomics replication experiments by Camerer et al. (2016), psychology replication experiments by the Open Science Collaboration (2015), and a metastudy by Wolfson and Belman (2015) on employment and the minimum wage.

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