ESMARConf2023: {metapack} tutorial

Presenter: Daeyoung Lim
Authors: Lim, Daeyoung; Chen, Ming-Hui; Ibrahim, Joseph G.; Kim, Sungduk; Shah, Arvind K.; Lin, Jianxin
Session: Tutorials 5
Title: metapack: Bayesian Meta-Regression and Network Meta-Regression
Abstract: Meta-analyses using study-level (or equivalently aggregate) data are of particular interest due to data availability and modeling flexibility. In this tutorial, we describe an R package metapack that introduces a unified formula interface for both meta-analysis and network meta-analysis, and explain how to use the formula interface. The user interface—and therefore the package—allows flexible variance-covariance modeling for multivariate meta-analysis models and univariate network meta-analysis models. Two meta-analytic data sets, cholesterol and TNM, included in the package are also introduced.
GitHub repository: https://github.com/daeyounglim/metapack