| plot.loglm | R Documentation | 
Visualize fitted "loglm" objects by mosaic or 
association plots.
## S3 method for class 'loglm'
plot(x, panel = mosaic, type = c("observed", "expected"),
  residuals_type = c("pearson", "deviance"), gp = shading_hcl, gp_args = list(),
  ...)
| x | a fitted  | 
| panel | a panel function for visualizing the observed values,
residuals and expected values. Currently,  | 
| 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  | 
| gp_args | list of arguments for the shading-generating function, if specified. | 
| ... | Other arguments passed to the  | 
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.
The "structable" visualized is returned invisibly.
Achim Zeileis Achim.Zeileis@R-project.org
loglm,
assoc,
mosaic,
strucplot
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_labs = c(Admit = 3)))
## and association plot
plot(fm, panel = assoc)
assoc(fm)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.