forest.netcomplex: Forest plot for complex interventions in component network...

View source: R/forest.netcomplex.R

forest.netcomplexR Documentation

Forest plot for complex interventions in component network meta-analysis

Description

Draws a forest plot in the active graphics window (using grid graphics system).

Usage

## S3 method for class 'netcomplex'
forest(
  x,
  pooled = ifelse(x$random, "random", "common"),
  leftcols = "studlab",
  leftlabs = NULL,
  rightcols = c("effect", "ci", "statistic", "pval"),
  rightlabs = c(NA, NA, "z", "p-value"),
  nchar.comps = x$nchar.trts,
  digits = gs("digits.forest"),
  digits.stat = gs("digits.stat"),
  digits.pval = gs("digits.pval"),
  smlab = NULL,
  backtransf = x$backtransf,
  lab.NA = ".",
  weight.study = "same",
  ...
)

## S3 method for class 'netcomplex'
plot(x, ...)

Arguments

x

An object of class netcomplex.

pooled

A character string indicating whether results for the common ("common") or random effects model ("random") should be plotted. Can be abbreviated.

leftcols

A character vector specifying (additional) columns to be plotted on the left side of the forest plot or a logical value (see forest.meta help page for details).

leftlabs

A character vector specifying labels for (additional) columns on left side of the forest plot (see forest.meta help page for details).

rightcols

A character vector specifying (additional) columns to be plotted on the right side of the forest plot or a logical value (see forest.meta help page for details).

rightlabs

A character vector specifying labels for (additional) columns on right side of the forest plot (see forest.meta help page for details).

nchar.comps

A numeric defining the minimum number of characters used to create unique names for components.

digits

Minimal number of significant digits for treatment effects and confidence intervals, see print.default.

digits.stat

Minimal number of significant digits for tests of overall effect, see print.default.

digits.pval

Minimal number of significant digits for p-value of overall effects, see print.default.

smlab

A label printed at top of figure. By default, text indicating either common or random effects model is printed.

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.

lab.NA

A character string to label missing values.

weight.study

A character string indicating weighting used to determine size of squares or diamonds.

...

Additional arguments for forest.meta function.

Details

A forest plot, also called confidence interval plot, is drawn in the active graphics window. For more information see help page of forest.meta function.

Author(s)

Guido Schwarzer sc@imbi.uni-freiburg.de

See Also

netcomplex, netcomb, discomb, forest.meta

Examples

data(Linde2016)

# Only consider studies including Face-to-face PST (to reduce
# runtime of example)
#
face <- subset(Linde2016, id %in% c(16, 24, 49, 118))

# Conduct random effects network meta-analysis
#
net1 <- netmeta(lnOR, selnOR, treat1, treat2, id,
  data = face, ref = "placebo", sm = "OR", common = FALSE)

# Additive model for treatment components (with placebo as inactive
# treatment)
#
nc1 <- netcomb(net1, inactive = "placebo")

# Some complex interventions
#
ints <- c("F + TCA", "F + Plac", "SSRI + Plac + TCA")
netcomplex(nc1, ints)
#
forest(netcomplex(nc1, ints))
forest(netcomplex(nc1, ints), nchar.comps = 4)

# Component effects
#
forest(netcomplex(nc1, nc1$comps))


netmeta documentation built on Nov. 4, 2022, 9:06 a.m.