Doing meta analysis with R : a hands on guide This book serves as an accessible introduction into how meta analyses can be conducted in R. Essential steps for meta analysis are covered including 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 SEM meta analysis are also covered. A companion R package dmetar is introduced in the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide