agreementplot | R Documentation |

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).

## 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)

`x` |
a confusion matrix, i.e., a table with equal-sized dimensions. |

`reverse_y` |
if |

`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 |

`newpage` |
logical; if |

`pop` |
logical; if |

`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 |

`data` |
a data frame (or list), or a contingency table from which
the variables in |

`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 |

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).

Invisibly returned, a list with components

`Bangdiwala` |
the unweighted agreement strength statistic. |

`Bangdiwala_Weighted` |
the weighted statistic. |

`weights` |
the weight vector used. |

David Meyer David.Meyer@R-project.org

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.

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)

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