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Extensions and additions to vcd: Visualizing Categorical Data

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vcdExtra

Extensions and additions to vcd: Visualizing Categorical Data

Version 0.7-3

This package provides additional data sets, documentation, and a few functions designed to extend the vcd package for Visualizing Categorical Data and the gnm package for Generalized Nonlinear Models. In particular, vcdExtra extends mosaic, assoc and sieve plots from vcd to handle glm() and gnm() models and adds a 3D version in mosaic3d().

vcdExtra is now a support package for the book Discrete Data Analysis with R by Michael Friendly and David Meyer.

Details

The main purpose of this package is to serve as a sandbox for introducing extensions of mosaic plots and related graphical methods that apply to loglinear models fitted using glm() and related, generalized nonlinear models fitted with gnm() in the gnm package. A related purpose is to fill in some holes in the analysis of categorical data in R, not provided in base R, vcd, or other commonly used packages.

  • The method mosaic.glm() extends the mosaic.loglm() method in the vcd package to this wider class of models. This method also works for the generalized nonlinear models fit with the gnm package, including models for square tables and models with multiplicative associations.

  • mosaic3d() introduces a 3D generalization of mosaic displays using the rgl package.

  • A new class, glmlist, is introduced for working with collections of glm objects, e.g., Kway() for fitting all K-way models from a basic marginal model, and LRstats() for brief statistical summaries of goodnes-of-fit for a collection of models.

  • For square tables with ordered factors, Crossings() supplements the specification of terms in model formulas using Symm(), Diag(), Topo(), etc. in the gnm package.

  • In addition, there are many new data sets, a tutorial vignette, Working with categorical data with R and the vcd package, vignette("vcd-tutorial", package = "vcdExtra"), and a few useful utility functions for manipulating categorical data sets and working with models for categorical data.

Installation

Get the released version from CRAN:

 install.packages("vcdExtra")

The development version can be installed to your R library directly from this repo via:

 if (!require(devtools)) install.packages("devtools")
 library(devtools)
 install_github("friendly/vcdExtra")

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