Identification of and Correction for Publication Bias

47 Pages Posted: 5 Apr 2017 Last revised: 27 Feb 2023

See all articles by Isaiah Andrews

Isaiah Andrews

Harvard Society of Fellows

Maximilian Kasy

University of California, Berkeley

Date Written: March 2017

Abstract

Some empirical results are more likely to be published than others. Such selective publication leads to biased estimates and distorted inference. This paper proposes 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 based on meta-studies. For known conditional publication probabilities, we propose median-unbiased estimators and associated confidence sets that correct for selective publication. We apply our methods to recent large-scale replication studies in experimental economics and psychology, and to meta-studies of the effects of minimum wages and de-worming programs.

Suggested Citation

Andrews, Isaiah and Kasy, Maximilian, Identification of and Correction for Publication Bias (March 2017). NBER Working Paper No. w23298, Available at SSRN: https://ssrn.com/abstract=2946704

Isaiah Andrews (Contact Author)

Harvard Society of Fellows ( email )

1875 Cambridge Street
Cambridge, MA 02138
United States

Maximilian Kasy

University of California, Berkeley ( email )

310 Barrows Hall
Berkeley, CA 94720
United States

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