In this post, we will sketch out what we think is a promising and pragmatic method for examining selective reporting while also accounting for effect size dependency. The method is to use a cluster-level bootstrap, which involves re-sampling clusters of observations to approximate the sampling distribution of an estimator. To illustrate this technique, we will demonstrate how to bootstrap a Vevea-Hedges selection model.
Meta-analysis is a set of statistical tools used to synthesize results from multiple studies evaluating a common research question. Two methodological challenges when conducting meta-analysis include selective reporting and correlated dependent …
Publication bias and other forms of outcome reporting bias are critical threats to the validity of findings from research syntheses. A variety of methods have been proposed for detecting selective outcome reporting in a collection of effect size …
Publication bias—or more generally, outcome reporting bias or dissemination bias—is recognized as a critical threat to the validity of findings from research syntheses. In the areas with which I am most familiar (education and psychology), it has become more or less a requirement for research synthesis projects to conduct analyses to detect the presence of systematic outcome reporting biases.