Addressing Selective Reporting Bias in Meta-Analysis of Dependent Effect Sizes: A Tutorial in R

• In Event: Advancing Meta-Analytic Methods

Abstract

Selective reporting arises when some research findings are selected to be reported, leading to biased estimates in meta-analysis. Various statistical methods have been proposed for dealing with selective reporting. However, few methods have been developed for handling selective reporting and publication bias in meta-analysis with dependent effect sizes, which are a common feature of meta-analyses in psychology. In this tutorial, we provide a guide to address selective reporting bias in the dependent effects context. We review several recently developed methods and demonstrate the implementation of these methods in the R statistical environment using data from two recent meta-analyses as examples. We discuss the application and interpretation of these methods, highlighting their strengths and limitations.

Authors

• Man Chen, University of Texas at Austin

• James E. Pustejovsky, University of Wisconsin - Madison