Provides meta-analysis methods that correct for
publication bias. Four methods are currently included in the package.
The p-uniform method as described in van Assen, van Aert, and Wicherts (2015)
The puniform package provides meta-analysis methods that correct for publication bias. Four methods are currently included in the package. The p-uniform method can be used for estimating the average effect size, testing the null hypothesis of no effect, and testing for publication bias using only the statistically significant effect sizes of primary studies. The second method in the package is the p-uniform* method. This method is an extension of the p-uniform method that allows for estimation of the average effect size and the between-study variance in a meta-analysis, and uses both the statistically significant and nonsignificant effect sizes. The third method in the package is the hybrid method. The hybrid method is a meta-analysis method for combining an original study and replication and while taking into account statistical significance of the original study. The p-uniform and hybrid method are based on the statistical theory that the distribution of p-values is uniform conditional on the population effect size. The fourth method in the package is the Snapshot Bayesian Hybrid Meta-Analysis Method. This method computes posterior probabilities for four true effect sizes (no, small, medium, and large) based on an original study and replication while taking into account publication bias in the original study. The method can also be used for computing the required sample size of the replication akin to power analysis in null hypothesis significance testing.
The latest release can be installed directly in R with:
You can install the development version of the puniform package from GitHub with:
Updated and improved documentation
Setting default parameters in puniform(), hybrid(), snapshot(), and puni_star() without losing backwards compatibility