vcd (version 1.4-4)

agreementplot: Bangdiwala's Observer Agreement Chart

Description

Representation of a \(k \times k\) 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 default
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",
              fill_col = function(j) gray((1 - (weights[j]) ^ 2) ^ 0.5),
              line_col = "red", xscale = TRUE, yscale = TRUE,
              return_grob = FALSE,
              prefix = "", …)
# S3 method for 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.

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.

return_grob

logical. Should a snapshot of the display be returned as a grid grob?

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.

fill_col

a function, giving the fill colors used for exact and partial agreement

line_col

color used for the diagonal reference line

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.

xscale, yscale

logicals indicating whether the marginals should be added on the x-axis/y-axis, respectively.

prefix

character string used as prefix for the viewport name

…

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 weight vector used.

Details

Weights can be specified to allow for partial agreement, taking into account contributions from off-diagonal cells. Partial agreement is typically represented in the display by lighter shading, as given by fill_col(j), corresponding to weights[j].

A weight vector of length 1 means strict agreement only, each additional element increases the maximum number of disagreement steps.

cotabplot can be used for stratified analyses (see examples).

References

Bangdiwala, S. I. (1988). The Agreement Chart. Department of Biostatistics, University of North Carolina at Chapel Hill, Institute of Statistics Mimeo Series No. 1859, http://www.stat.ncsu.edu/information/library/mimeo.archive/ISMS_1988_1859.pdf

Bangdiwala, S. I., Ana S. Haedo, Marcela L. Natal, and Andres Villaveces. The agreement chart as an alternative to the receiver-operating characteristic curve for diagnostic tests. Journal of Clinical Epidemiology, 61 (9), 866-874.

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

Examples

# NOT RUN {
data("SexualFun")
agreementplot(t(SexualFun))

data("MSPatients")
# }
# NOT RUN {
## 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()
# }
# NOT RUN {
## alternatively, use cotabplot:
cotabplot(MSPatients, panel = cotab_agreementplot)
# }