structable: Structured Contingency Tables

In vcd: Visualizing Categorical Data

Structured Contingency Tables

Description

This function produces a ‘flat’ representation of a high-dimensional contingency table constructed by recursive splits (similar to the construction of mosaic displays).

Usage

## S3 method for class 'formula'
structable(formula, data,
direction = NULL, split_vertical = NULL, ..., subset, na.action)
## Default S3 method:
structable(..., direction = NULL, split_vertical = FALSE)

Arguments

formula	a formula object with possibly both left and right hand sides specifying the column and row variables of the flat table.
data	a data frame, list or environment containing the variables to be cross-tabulated, or an object inheriting from class table.
subset	an optional vector specifying a subset of observations to be used. Ignored if data is a contingency table.
na.action	a function which indicates what should happen when the data contain NAs. Ignored if data is a contingency table
...	R objects which can be interpreted as factors (including character strings), or a list (or data frame) whose components can be so interpreted, or a contingency table object of class "table" or "ftable".
split_vertical	logical vector indicating, for each dimension, whether it should be split vertically or not (default: FALSE). Values are recycled as needed. If the argument is of length 1, the value is alternated for all dimensions. Ignored if direction is provided.
direction	character vector alternatively specifying the splitting direction ("h" for horizontal and "v" for vertical splits). Values are recycled as needed. If the argument is of length 1, the value is alternated for all dimensions.

Details

This function produces textual representations of mosaic displays, and thus ‘flat’ contingency tables. The formula interface is quite similar to the one of ftable, but also accepts the mosaic-like formula interface (empty left-hand side). Note that even if the ftable interface is used, the split_vertical or direction argument is needed to specify the order of the horizontal and vertical splits. If pretabulated data with a Freq column is used, than the left-hand side should be left empty—the Freq column will be handled correctly.

"structable" objects can be subset using the [ and [[ operators, using either level indices or names (see examples). The corresponding replacement functions are available as well. In addition, appropriate aperm, cbind, rbind, length, dim, and is.na methods do exist.

Value

An object of class "structable", inheriting from class "ftable", with the splitting information ("split_vertical") as additional attribute.

Author(s)

David Meyer [e-mail]

References

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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v017.i03")} and available as vignette("strucplot").

See Also

strucplot, mosaic, ftable

Examples

structable(Titanic)
structable(Titanic, split_vertical = c(TRUE, TRUE, FALSE, FALSE))
structable(Titanic, direction = c("h","h","v","v"))
structable(Sex + Class ~ Survived + Age, data = Titanic)

## subsetting of structable objects
(hec <- structable(aperm(HairEyeColor)))

## The "[" operator treats structables as a block-matrix and selects parts of the matrix:
hec[1]
hec[2]
hec[1,c(2,4)]
hec["Male",c("Blue","Green")]

## replacement funcion:
tmp <- hec
(tmp[1,2:3] <- tmp[2,c(1,4)])

## In contrast, the "[[" operator treats structables as two-dimensional
## lists. Indexing conditions on specified levels and thus reduces the dimensionality:

## seek subtables conditioning on levels of the first dimension:
hec[[1]]
hec[[2]]

## Seek subtable from the first two dimensions, given the level "Male"
## of the first variable, and "Brown" from the second
## (the following two commands are equivalent):
hec[["Male"]][["Brown"]]
hec[[c("Male","Brown")]]

## Seeking subtables by conditioning on row and/or column variables:
hec[["Male","Hazel"]]
hec[[c("Male","Brown"),]]
hec[[c("Male","Brown"),"Hazel"]]

## a few other operations
t(hec)
dim(hec)
dimnames(hec)
as.matrix(hec)
length(hec)
cbind(hec[,1],hec[,3])

as.vector(hec) ## computed on the _multiway_ table
as.vector(unclass(hec))

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