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).
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.
The stable release of NMAforest can be installed from CRAN:
install.packages("NMAPropForest")
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 (used instead of
event ) |
numeric |
study |
All analyses | Study label or grouping variable | character or numeric |
id |
Optional | Unique numeric study identifier (auto-generated if missing) | integer |
Note: We recommend that users include an explicit
id
column where each value uniquely corresponds to a study
label in the study
column.
If the id
column is not present in the dataset, the
function will automatically generate one and return the updated data
frame with this column added.