Doing Meta-Analysis with R av Mathias Cuijpers Pim Furukawa Toshi Eber Harrer

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<p><strong>Doing Meta-Analysis with R: A Hands-On Guide</strong> serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, <i>dmetar</i>, is introduced at the beginning of the guide. It contains data sets and several helper functions for the <i>meta</i> and <i>metafor</i> package used in the guide. </p><p>The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. </p><b></b><p><b>Features</b><br>¿ Contains two introductory chapters on how t