heatplot.netmeta: Heat Plot

In netmeta: Network Meta-Analysis using Frequentist Methods

Heat Plot

Description

Produces a heat plot containing treatment estimates with confidence intervals for all possible pairwise comparisons.

Usage

## S3 method for class 'netmeta'
heatplot(
  x,
  pooled = ifelse(x$random, "random", "common"),
  seq = x$seq,
  nchar.trts = x$nchar.trts,
  low.colour = "red",
  mid.colour = "white",
  high.colour = "springgreen4",
  size = 6,
  size.trt = 16,
  size.axis = 12,
  digits = gs("digits.forest"),
  backtransf = x$backtransf,
  ...
)

Arguments

x	An object of class netmeta.
pooled	A character string indicating whether results for the common ("common") or random effects model ("random") should be plotted. Can be abbreviated.
seq	A character or numerical vector specifying the sequence of treatments in rows and columns of the heat plot.
nchar.trts	A numeric defining the minimum number of characters used to create unique treatment names.
low.colour	A string indicating the colour of low relative treatment effects for the heat plot (e.g odds ratio of ~0.5)
mid.colour	A string indicating the colour of null relative treatment effects for the heat plot (e.g odds ratio of ~1.0).
high.colour	A string indicating the colour of high relative treatment effects for the heat plot (e.g odds ratio of ~2.0).
size	The size of cell entries with the relative treatment effect and confidence intervals.
size.trt	The size of treatment names placed on the top and left of the plot.
size.axis	The size of labels on the top and left of the plot
digits	Minimal number of significant digits for treatment effects and confidence intervals, see print.default.
backtransf	A logical indicating whether results should be back transformed in forest plots. If backtransf = TRUE, results for sm = "OR" are presented as odds ratios rather than log odds ratios, for example.
...	Additional arguments.

Value

League heat plot, where a color scale is used to represent the values of relative treatment effects.

Examples

# Only consider first five studies (to reduce runtime of example)
#
studies <- unique(Senn2013$study)
Senn2013.5 <- subset(Senn2013, study %in% studies[1:5])

# Transform data from long arm-based to contrast-based format
#
pw <- pairwise(studlab = study, treat = treatment,
  n = n, mean = mean, sd = sd, data = Senn2013.5,
  varnames = c("MD", "seMD"))

# Conduct random effects network meta-analysis with
# placebo as reference treatment
#
nma <- netmeta(pw, common = FALSE, reference = "plac")

# Generate a heat plot (with abbreviated treatment labels)
#
heatplot(nma, nchar.trts = 4) 

netmeta documentation built on April 11, 2026, 9:06 a.m.