Produce a forest plot. Includes graphical summary of results if applied to output of suitable model-fitting function.
forest methods for
madauni objects are provided.
## S3 method for class 'madad': forest((x, type = "sens", log = FALSE, ...)) ## S3 method for class 'madauni': forest((x, log = TRUE, ...) forestmada(x, ci, plotci = TRUE, main = "Forest plot", xlab = NULL, digits = 2L, snames = NULL, subset = NULL, pch = 15, cex = 1, cipoly = NULL, polycol = NA, ...))
- an object for which a
forestmethod exists or (in the case of
foresmada) a vector of point estimates.
- numeric matrix, each row corresponds to a confidence interval (the first column being the lower bound and the second the upper).
- logical, should the effects sizes and their confidence intervals be added to the plot (as text)?
- character, heading of plot.
- label of x-axis.
- integer, number of digits for axis labels and confidence intervals.
- character vector, study names. If
NULL, generic study names are generated.
- integer vector, allows to study only a subset of studies in the plot. One can also reorder the studies with the help of this argument.
- integer, plotting symbol, defaults to a small square. Also see
- numeric, scaling parameter for study names and confidence intervals.
- logical vector, which confidence interval should be plotted as a polygon? Useful for summary estimates. If set to
NULL, regular confidence intervals will be used.
- color of the polygon(s), passed on to
polygon. The default value of
NAimplies no color.
- character, one of
- logical, should the log-transformed values be plotted?
- arguments to be passed on to
forestmadaand further on to other plotting functions
Produces a forest plot to graphically assess heterogeneity. Note that
forestmada is called internally, so that the
... argument can be used to pass on arguments to this function; see the examples.
Returns and invisible
data(AuditC) ## Forest plot of log DOR with random effects summary estimate forest(madauni(AuditC)) ## Forest plot of negative likelihood ratio (no log transformation) ## color of the polygon: light grey ## draw the individual estimate as filled circles forest(madauni(AuditC, type = "negLR"), log = FALSE, polycol = "lightgrey", pch = 19) ## Paired forest plot of sensitivities and specificities ## Might look ugly if device region is too small old.par <- par() AuditC.d <- madad(AuditC) plot.new() par(fig = c(0, 0.5, 0, 1), new = TRUE) forest(AuditC.d, type = "sens", xlab = "Sensitivity") par(fig = c(0.5, 1, 0, 1), new = TRUE) forest(AuditC.d, type = "spec", xlab = "Specificity") par(old.par) ## Including study names ## Using Letters as dummies forest(AuditC.d, type = "spec", xlab = "Specificity", snames = LETTERS[1:14])
Documentation reproduced from package mada, version 0.5.5. License: GPL-2