vcd (version 0.1-3.5)

agreementplot.default: Bangdiwala's Observer Agreement Chart

Description

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).

Usage

## S3 method for class 'default':
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)

Arguments

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).

Value

• Invisibly returned, a list with components
• Bangdiwala
  the unweighted agreement strength statistic
• Bangdiwala.Weighted
  the weighted statistic
• weights
  the weigtht vector used.

Details

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.

References

Michael Friendly (2000), Visualizing Categorical Data. SAS Institute, Cary, NC.

Examples

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))