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APS

29th APS Annual Convention · 2017

A Bayesian Framework to Mitigate Publication Bias in Meta-Analyses

Boston, MA · May 2017

Poster Session · Methodology

  • Alexander Etz
    University of California, Irvine
  • Joachim Vandekerckhove
    University of California, Irvine

Abstract

Bayesian bias correction is a novel method for evaluating evidence in published papers in the presence of publication bias. The original method by Guan and Vandekerckhove (2016) is limited to sets of studies with homogeneous effect sizes. We develop an hierarchical extension to allow for heterogeneous effect sizes.

Quantitative

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