pairs.table {vcd} | R Documentation

## Pairs Plot for Contingency Tables

### Description

Produces a matrix of strucplot displays.

### Usage

    ## S3 method for class 'table':
    pairs(x, upper_panel = pairs_mosaic, upper_panel_args = list(),
      lower_panel = pairs_mosaic, lower_panel_args = list(),
      diag_panel = pairs_barplot, diag_panel_args = list(),
      main = NULL, title_gp = gpar(fontsize = 20), space = 0.1,
      newpage = TRUE, ...)

### Arguments

`x` | a contingency table in array form, with optional category labels specified in the `dimnames(x)` attribute.
`upper_panel` | function for the upper triangle of the matrix, or corresponding generating function. If `NULL`, no panel is drawn.
`upper_panel_args` | list of arguments for the generating function, if specified.
`lower_panel` | function for the lower triangle of the matrix, or corresponding generating function. If `NULL`, no panel is drawn.
`lower_panel_args` | list of arguments for the panel-generating function, if specified.
`diag_panel` | function for the diagonal of the matrix, or corresponding generating function. If `NULL`, no panel is drawn.
`diag_panel_args` | list of arguments for the generating function, if specified.
`main` | character string specifying the main title.
`title_gp` | object of class `"gpar"` used for the title.
`space` | double specifying the distance between the cells.
`newpage` | logical controlling whether a new grid page should be created.
`...` | For convenience, list of arguments for the panel-generating functions of upper and lower panels, if specified.

### Details

This is a `pairs` method for objects inheriting from class `"table"` or `"structable"`. It plots a matrix of pairwise mosaic plots.

Four independence types are distinguished: `"pairwise"`, `"total"`, `"conditional"` and `"joint"`. The pairwise mosaic matrix shows bivariate marginal relations, collapsed over all other variables. The total independence mosaic matrix shows mosaic plots for mutual independence, i.e., for marginal and conditional independence among all pairs of variables. The conditional independence mosaic matrix shows mosaic plots for marginal independence given all other variables. The joint independence mosaic matrix shows mosaic plots for joint independence of all pairs of variables from the others.

This method uses panel functions called for each cell of the matrix which can be different for upper matrix, lower matrix, and diagonal cells. Correspondingly, for each panel parameter foo (= `upper`, `lower`, or `diag`), `pairs.table` takes two arguments: foo_panel and foo_panel_args, which can be used to specify the parameters as follows:

1. Passing a suitable panel function to foo_panel which subsequently is called for each cell with the corresponding coordinates.
2. Passing a corresponding generating function (of class `"panel_generator"`) to foo_panel, along with parameters passed to foo_panel_args, that generates such a function.

Hence, the second approach is equivalent to the first if foo_panel(foo_panel_args) is passed to foo_panel.

### Author(s)

David Meyer David.Meyer@R-project.org

### References

Cohen, A. (1980), On the graphical display of the significant components in a two-way contingency table. Communications in Statistics—Theory and Methods, A9, 1025–1041.

Friendly, M. (1992), Graphical methods for categorical data. SAS User Group International Conference Proceedings, 17, 190–200. http://www.math.yorku.ca/SCS/sugi/sugi17-paper.html

### See Also

`pairs_mosaic`, `pairs_assoc`, `pairs_sieve`, `pairs_diagonal_text`, `pairs_text`, `pairs_barplot`, `assoc`, `sieve`, `mosaic`

### Examples

    data(UCBAdmissions)
    data(PreSex)

    pairs(PreSex)
    pairs(UCBAdmissions)
    pairs(UCBAdmissions, upper_panel_args = list(shade = TRUE))
    pairs(UCBAdmissions, lower_panel = pairs_mosaic(type = "conditional"))
    pairs(UCBAdmissions, diag_panel = pairs_text)
    pairs(UCBAdmissions, upper_panel = pairs_assoc, shade = TRUE)

[Package vcd version 0.9-6 Index]