Forest Plots for Network Meta-Analysis with Proportion for Paths and Studies.
NMAforest
NMAforest is an R package for generating detailed forest plots in network meta-analysis (NMA). It visualizes direct, indirect, and network meta-analysis treatment effects, along with study- and path-level contribution proportions. The visualization is based on the evidence flow decomposition method by Papakonstantinou et al. (2018).
Acknowledgments
This package relies on key infrastructure from the netmeta, igraph, and ggplot2 R packages.
It also adapts methods and code presented by Papakonstantinou et al. (2018) for evidence flow decomposition in network meta-analysis, including the comparisonStreams() function from the flow_contribution GitHub repository.
Installation
The stable release of NMAforest can be installed from CRAN:
install.packages("NMAPropForest")
Required Data Format
The following columns are required (either with these names or specified via function arguments):
| Column | Required For | Description | Type |
|---|---|---|---|
treat | All analyses | Treatment label for each arm | character or factor |
event | Binary outcomes | Number of events in the arm | numeric |
n | All analyses | Sample size in each arm | numeric |
mean, sd | Continuous outcomes | Mean and standard deviation | numeric |
study | All analyses | Study label or grouping variable | character or numeric |
study_id | Optional | Unique numeric study identifier (auto-generated if missing) | integer |
Note: We recommend that users include an explicit study_id column where each value uniquely corresponds to a study label in the study column.
If the study_id column is not present in the dataset, the function will automatically generate one and return the updated data frame with this column added.