Forest plot for orbbound object (bound for outcome reporting bias)
Draws a forest plot in the active graphics window (using grid graphics system).
## S3 method for class 'orbbound'
forest(
x,
comb.fixed = x$x$comb.fixed,
comb.random = x$x$comb.random,
text.fixed = "FE model",
text.random = "RE model",
smlab = NULL,
leftcols = c("studlab", "maxbias"),
leftlabs = c("Missing\nstudies", "Maximum\nbias"),
backtransf = x$backtransf,
digits = max(3, .Options$digits - 3),
...
)x |
An object of class |
comb.fixed |
A logical indicating whether sensitivity analysis for fixed effect model should be plotted. |
comb.random |
A logical indicating whether sensitivity analysis for random effects model should be plotted. |
text.fixed |
A character string used in the plot to label subgroup with results for fixed effect model. |
text.random |
A character string used in the plot to label subgroup with results for random effects model. |
smlab |
A label printed at top of figure. If only results for either fixed effect or random effects model is plotted, text indicates which model was used. |
leftcols |
A character vector specifying (additional) columns
to be plotted on the left side of the forest plot or a logical
value (see |
leftlabs |
A character vector specifying labels for
(additional) columns on left side of the forest plot (see
|
backtransf |
A logical indicating whether results should be
back transformed in printouts and plots. If
|
digits |
Minimal number of significant digits, see
|
... |
Additional arguments for |
A forest plot, also called confidence interval plot, is drawn in the active graphics window.
For relative effect measures, e.g., 'RR', 'OR', and 'HR', the
column labeled "Maximum bias" contains the relative bias, e.g. a
value of 1.10 means a maximum overestimation by 10 percent. If
backtransf=FALSE for these summary measures, maximum bias is
instead printed as absolute bias.
Internally, R function forest.meta is called to
create a forest plot. For more information see help page of the
forest.meta function.
Guido Schwarzer sc@imbi.uni-freiburg.de
data(Fleiss1993bin, package = "meta") m1 <- metabin(d.asp, n.asp, d.plac, n.plac, data = Fleiss1993bin, sm = "OR") orb1 <- orbbound(m1, k.suspect = 1:5) print(orb1, digits = 2) forest(orb1, xlim = c(0.7, 1.5)) ## Not run: forest(orb1, backtransf = FALSE)
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