PUB_BIAS: A SAS ® Macro for Detecting Publication Bias in Meta-Analysis

Abstract

Publication bias is one threat to validity that researchers conducting meta-analysis studies confront. Although statistical methods for detecting publication bias have surfaced in the literature (e.g., Begg Rank Correlation, Egger Regression, Funnel Plot Regression, and Trim & Fill), many researchers rely on visual inspection of funnel plots. This program was created to provide meta-analysts with the ability to implement statistical methods to detect publication bias. Statistical information from the corpus of studies (i.e., effect sizes and sample sizes) is input in this SAS macro and analyzed for potential publication bias using the above mentioned statistical methods. In addition to the p-value associated with each detection method the program output provides the estimated mean effect size and random effects variance component. The application of the SAS/IML programming on two sets of example data (with and without publication bias) is provided along with the macro programming language.