Study specific prediction intervals for random-effects meta-analysis: A tutorial: Prediction intervals in meta-analysis.

ABSTRACT: The pooled estimate of the average effect is of primary interest when fitting the random-effects model for meta-analysis. However estimates of study specific effects, for example those displayed on forest plots, are also often of interest. In this tutorial, we present the case, with the accompanying statistical theory, for estimating the study specific true effects using so called 'empirical Bayes estimates' or 'Best Unbiased Linear Predictions' under the random-effects model. These estimates can be accompanied by prediction intervals that indicate a plausible range of study specific true effects. We coalesce and elucidate the available literature and illustrate the methodology using two published meta-analyses as examples. We also perform a simulation study that reveals that coverage prob

SUBMITTER: van Aert RCM 

PROVIDER: S-EPMC8361666 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature