forest.metainf: Forest plot to display the result of a leave-one-out meta-analysis

Description

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

Usage

# S3 method for metainf
forest(
  x,
  prediction = x$prediction,
  overall = x$overall,
  just.addcols = "right",
  smlab = "Leave-One-Out Meta-Analysis",
  type = "square",
  layout = gs("layout"),
  lab.NA = ".",
  backtransf = x$backtransf,
  big.mark = gs("big.mark"),
  digits = gs("digits.forest"),
  digits.pval = gs("digits.pval"),
  digits.tau2 = gs("digits.tau2"),
  digits.tau = gs("digits.tau"),
  digits.I2 = gs("digits.I2"),
  digits.cid = gs("digits.cid"),
  digits.percent = 1,
  col = gs("col.study"),
  col.bg = ifelse(type == "diamond", gs("col.diamond"), gs("col.square")),
  col.border = ifelse(type == "diamond", gs("col.diamond.lines"), gs("col.square.lines")),
  col.bg.predict = gs("col.predict"),
  col.border.predict = gs("col.predict.lines"),
  addrows.below.overall = 1L * details,
  details = gs("forest.details"),
  ...
)

Arguments

x: An object of class metainf.
prediction: A logical indicating whether prediction intervals should be printed.
overall: A logical indicating whether overall results should be shown.
just.addcols: Justification of text for additional columns (possible values: "left", "right", "center").
smlab: A label for the summary measure (printed at top of figure).
type: A character string or vector specifying how to plot treatment effects and confidence intervals for cumulative meta-analysis results.
layout: A character string specifying the layout of the forest plot (see forest.meta).
lab.NA: A character string to label missing values.
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.
big.mark: A character used as thousands separator.
digits: Minimal number of significant digits for treatment effects, see print.default.
digits.pval: Minimal number of significant digits for p-values.
digits.tau2: Minimal number of significant digits for between-study variance.
digits.tau: Minimal number of significant digits for square root of between-study variance.
digits.I2: Minimal number of significant digits for I-squared statistic.
digits.cid: Minimal number of significant digits for CID / decision thresholds, see print.default.
digits.percent: Minimal number of significant digits for probabilities, printed as percentages, see print.default.
col: The colour for cumulative meta-analysis results (only considered if type = "square").
col.bg: The background colour for squares and diamonds of cumulative meta-analysis results.
col.border: The colour for the outer lines of squares and diamonds of cumulative meta-analysis results.
col.bg.predict: The background colour for prediction intervals of cumulative meta-analysis results.
col.border.predict: The colour for the outer lines of prediction intervals of cumulative meta-analysis results.
addrows.below.overall: A numeric value indicating how many empty rows are printed between meta-analysis results and meta-analysis details.
details: A logical specifying whether details on statistical methods should be printed.
...: Additional graphical arguments (passed on to forest.meta).

Author

Guido Schwarzer guido.schwarzer@uniklinik-freiburg.de

Details

A forest plot, also called confidence interval plot, is drawn in the active graphics window. Internally, R function forest.metacum is called to produce the forest plot.

Examples

Run this code

data(Fleiss1993bin)
m1 <- metabin(d.asp, n.asp, d.plac, n.plac,
  data = Fleiss1993bin, studlab = study, sm = "RR", method = "I")
m1
metainf(m1)
metainf(m1, pooled = "random")

forest(metainf(m1))
forest(metainf(m1, pooled = "random"))
forest(metainf(m1, pooled = "random", prediction = TRUE))