R: Visualize Fitted Log-linear Models

plot.loglm {vcd} | R Documentation

## Visualize Fitted Log-linear Models

### Description

Visualize fitted `"loglm"` objects by mosaic or association plots.

### Usage

    ## S3 method for class 'loglm'
    plot(x, panel = mosaic, type = c("observed", "expected"),
      residuals_type = c("pearson", "deviance"), gp = shading_hcl, gp_args = list(),
      ...)

### Arguments

`x` | a fitted `"loglm"` object, see `loglm`.
`panel` | a panel function for visualizing the observed values, residuals and expected values. Currently, `mosaic` and `assoc` in vcd.
`type` | a character string indicating whether the observed or the expected values of the table should be visualized.
`residuals_type` | a character string indicating the type of residuals to be computed.
`gp` | object of class `"gpar"`, shading function or a corresponding generating function (see details and `shadings`). Ignored if `shade = FALSE`.
`gp_args` | list of arguments for the shading-generating function, if specified.
`...` | Other arguments passed to the `panel` function.

### Details

The `plot` method for `"loglm"` objects by default visualizes the model using a mosaic plot (can be changed to an association plot by setting `panel = assoc`) with a shading based on the residuals of this model. The legend also reports the corresponding p value of the associated goodness-of-fit test. The `mosaic` and `assoc` methods are simple convenience interfaces to this `plot` method, setting the `panel` argument accordingly.

### Value

The `"structable"` visualized is returned invisibly.

### Author(s)

Achim Zeileis Achim.Zeileis@R-project.org

### See Also

`loglm`, `assoc`, `mosaic`, `strucplot`

### Examples

    library(MASS)
    ## mosaic display for PreSex model
    data("PreSex")
    fm <- loglm(~ PremaritalSex * ExtramaritalSex * (Gender + MaritalStatus),
      data = aperm(PreSex, c(3, 2, 4, 1)))
    fm
    ## visualize Pearson statistic
    plot(fm, split_vertical = TRUE)
    ## visualize LR statistic
    plot(fm, split_vertical = TRUE, residuals_type = "deviance")

    ## conditional independence in UCB admissions data
    data("UCBAdmissions")
    fm <- loglm(~ Dept * (Gender + Admit), data = aperm(UCBAdmissions))

    ## use mosaic display
    plot(fm, labeling_args = list(abbreviate = c(Admit = 3)))

    ## and association plot
    plot(fm, panel = assoc)
    assoc(fm)

[Package vcd version 1.4-4 Index]