ESMARConf2023: {metavcov} tutorial

Presenter: Min Lu
Authors: Lu, Min
Session: Tutorials 4
Title: Conducting Multivariate Meta-Analysis in R with metavcov
Abstract: Multivariate meta-analysis (MMA) handles within-study dependence among effect sizes caused by the fact that multiple outcomes were obtained from the same participants in the primary studies. The metavcov package aims for model preparation, data visualization and missing data solutions. It provides sufficient constructs for estimating coefficients from other well-established packages. For model preparation, users can compute effect sizes and their variance-covariance matrices of various types, including correlation coefficients, standardized mean difference, mean difference, log odds ratio, log risk ratio, and risk difference. The package provides a tool to plot the confidence intervals for the primary studies and the overall estimators. When specific effect sizes are missing, single imputation is possible in the model preparation stage, while the multiple imputation method is also available for pooling the results in a statistically principled manner from models of users' choice. The package is demonstrated on two datasets with an example for handling missing data. For model fitting, packages mixmeta and metaSEM are used in the demonstration.
GitHub repository: luminwin.githu...
Links: esmarconf.org/...
esmarconf.org/...