agreementplot {vcd} | R Documentation |
Representation of a k by k confusion matrix, where the observed and expected diagonal elements are represented by superposed black and white rectangles, respectively. The function also computes a statistic measuring the strength of agreement (relation of respective area sums).
## Default S3 method: agreementplot(x, reverse_y = TRUE, main = NULL, weights = c(1, 1 - 1/(ncol(x) - 1)^2), margins = par("mar"), newpage = TRUE, pop = TRUE, xlab = names(dimnames(x))[2], ylab = names(dimnames(x))[1], xlab_rot = 0, xlab_just = "center", ylab_rot = 90, ylab_just = "center", ...) ## S3 method for class 'formula': agreementplot(formula, data = NULL, ..., subset)
x |
a confusion matrix, i.e., a table with equal-sized dimensions. |
reverse_y |
if TRUE , the y axis is reversed (i.e., the
rectangles' positions correspond to the contingency table). |
main |
user-specified main title. |
weights |
vector of weights for successive larger observed areas, used in the agreement strength statistic, and also for the shading. The first element should be 1. |
margins |
vector of margins (see par ). |
newpage |
logical; if TRUE , the plot is drawn on a new page. |
pop |
logical; if TRUE , all newly generated viewports are popped after plotting. |
xlab, ylab |
labels of x- and y-axis. |
xlab_rot, ylab_rot |
rotation angle for the category labels. |
xlab_just, ylab_just |
justification for the category labels. |
formula |
a formula, such as y ~ x .
For details, see xtabs . |
data |
a data frame (or list), or a contingency table from which
the variables in formula should be taken. |
subset |
an optional vector specifying a subset of the rows in the data frame to be used for plotting. |
... |
further graphics parameters (see par ). |
Weights can be specified to allow for partial agreement, taking into account contributions from off-diagonal cells. A weight vector of length 1 means strict agreement only, each additional element increases the maximum number of disagreement steps.
Invisibly returned, a list with components
Bangdiwala |
the unweighted agreement strength statistic. |
Bangdiwala_Weighted |
the weighted statistic. |
weights |
the weigtht vector used. |
David Meyer David.Meyer@R-project.org
Michael Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.
data("SexualFun") agreementplot(t(SexualFun)) data("MSPatients") ## best visualized using a resized device, e.g. using: ## get(getOption("device"))(width = 12) pushViewport(viewport(layout = grid.layout(ncol = 2))) pushViewport(viewport(layout.pos.col = 1)) agreementplot(t(MSPatients[,,1]), main = "Winnipeg Patients", newpage = FALSE) popViewport() pushViewport(viewport(layout.pos.col = 2)) agreementplot(t(MSPatients[,,2]), main = "New Orleans Patients", newpage = FALSE) popViewport(2) dev.off()