agreementplot: Bangdiwala's Observer Agreement Chart

In vcd: Visualizing Categorical Data

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

## 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",
              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 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.
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).

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).

Value

Invisibly returned, a list with components

Bangdiwala	the unweighted agreement strength statistic.
Bangdiwala_Weighted	the weighted statistic.
weights	the weight vector used.

Author(s)

David Meyer [e-mail]

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, https://repository.lib.ncsu.edu/bitstreams/fea554e9-8750-4f1a-8419-ee126ce1a790/download

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

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()

## End(Not run)

## alternatively, use cotabplot:
cotabplot(MSPatients, panel = cotab_agreementplot)

vcd documentation built on Sept. 17, 2024, 1:08 a.m.