agreementplot.default {vcd} | R Documentation |
Representation of a k x 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 = "Agreement Chart", weights = c(1, 1 - 1/(ncol(x) - 1)^2), cex.main = 2, cex.lab = 1.5, xlab = names(dimnames(x))[2], ylab = names(dimnames(x))[1], ...) ## 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. |
cex.main |
font size of title. |
cex.lab |
font size of labels. |
xlab, ylab |
labels of x- and y-axis. |
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 observations 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@ci.tuwien.ac.at
Michael Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.
data(SexualFun) agreementplot(t(SexualFun)) data(MSPatients) ## Enlarge plot manually or use sth. like: X11(width = 12)! par(mfrow = c(1,2)) agreementplot(t(MSPatients[,,1]), main = "Winnipeg Patients") agreementplot(t(MSPatients[,,2]), main = "New Orleans Patients") par(mfrow = c(1,1))