This function creates a doubledecker plot visualizing a classification rule.

```
# S3 method for formula
doubledecker(formula, data = NULL, ..., main = NULL)
# S3 method for default
doubledecker(x, depvar = length(dim(x)),
margins = c(1,4, length(dim(x)) + 1, 1),
gp = gpar(fill = rev(gray.colors(tail(dim(x), 1)))),
labeling = labeling_doubledecker,
spacing = spacing_highlighting,
main = NULL, keep_aspect_ratio = FALSE, ...)
```

The `"structable"`

visualized is returned invisibly.

- formula
a formula specifying the variables used to create a contingency table from

`data`

. The dependent variable is used last for splitting.- data
either a data frame, or an object of class

`"table"`

or`"ftable"`

.- x
a contingency table in array form, with optional category labels specified in the

`dimnames(x)`

attribute.- depvar
dimension index or character string specifying the dependent variable. That will be sorted last in the table.

- margins
margins of the plot. Note that by default, all factor names (except the last one) and their levels are visualized

*as a block*under the plot.- gp
object of class

`"gpar"`

used for the tiles of the last variable.- labeling
labeling function or corresponding generating generating function (see

`strucplot`

for details).- spacing
spacing object, spacing function or corresponding generating function (see

`strucplot`

for details).- main
either a logical, or a character string used for plotting the main title. If

`main`

is`TRUE`

, the name of the`data`

object is used.- keep_aspect_ratio
logical indicating whether the aspect ratio should be maintained or not.

- ...
Further parameters passed to

`mosaic`

.

David Meyer David.Meyer@R-project.org

Doubledecker plots visualize the the dependence of one categorical (typically binary) variable on further categorical variables. Formally, they are mosaic plots with vertical splits for all dimensions (antecedents) except the last one, which represents the dependent variable (consequent). The last variable is visualized by horizontal splits, no space between the tiles, and separate colors for the levels.

H. Hoffmann (2001),
Generalized odds ratios for visual modeling.
*Journal of Computational and Graphical Statistics*,
**10**, 4, 628--640.

Meyer, D., Zeileis, A., and Hornik, K. (2006),
The strucplot framework: Visualizing multi-way contingency tables with
vcd.
*Journal of Statistical Software*, **17(3)**, 1-48.
tools:::Rd_expr_doi("10.18637/jss.v017.i03") and available as
`vignette("strucplot")`

.

`strucplot`

,
`mosaic`

```
data("Titanic")
doubledecker(Titanic)
doubledecker(Titanic, depvar = "Survived")
doubledecker(Survived ~ ., data = Titanic)
```

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