vcd: agreementplot – R documentation

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agreementplot

Bangdiwala's Observer Agreement Chart

Description

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).

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 David.Meyer@R-project.org

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/bitstream/handle/1840.4/3827/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

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

Visualizing Categorical Data

v1.4-10

GPL-2

Authors

David Meyer [aut, cre], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Kurt Hornik [aut], Florian Gerber [ctb], Michael Friendly [ctb]

Initial release