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% File src/library/graphics/man/assocplot.Rd

% Part of the R package, http://www.R-project.org

% Copyright 1995-2007 R Core Team

% Distributed under GPL 2 or later

\newcommand{\CRANpkg}{\href{http://CRAN.R-project.org/package=#1}{\pkg{#1}}}

\name{assocplot}

\alias{assocplot}

\encoding{UTF-8}

\title{Association Plots}

\description{

  Produce a Cohen-Friendly association plot indicating deviations from

  independence of rows and columns in a 2-dimensional contingency

  table.

}

\usage{

assocplot(x, col = c("black", "red"), space = 0.3,

          main = NULL, xlab = NULL, ylab = NULL)

}

\arguments{

  \item{x}{a two-dimensional contingency table in matrix form.}

  \item{col}{a character vector of length two giving the colors used for

    drawing positive and negative Pearson residuals, respectively.}

  \item{space}{the amount of space (as a fraction of the average

    rectangle width and height) left between each rectangle.}

  \item{main}{overall title for the plot.}

  \item{xlab}{a label for the x axis.  Defaults to the name (if any) of

    the row dimension in \code{x}.}

  \item{ylab}{a label for the y axis.  Defaults to the name (if any) of

    the column dimension in \code{x}.}

}

\details{

  For a two-way contingency table, the signed contribution to Pearson's

  \eqn{\chi^2}{chi^2} for cell \eqn{i, j} is \eqn{d_{ij} = (f_{ij} -

    e_{ij}) / \sqrt{e_{ij}}}{d_{ij} = (f_{ij} - e_{ij}) / sqrt(e_{ij})},

  where \eqn{f_{ij}} and \eqn{e_{ij}} are the observed and expected

  counts corresponding to the cell.  In the Cohen-Friendly association

  plot, each cell is represented by a rectangle that has (signed) height

  proportional to \eqn{d_{ij}} and width proportional to

  \eqn{\sqrt{e_{ij}}}{sqrt(e_{ij})}, so that the area of the box is

  proportional to the difference in observed and expected frequencies.

  The rectangles in each row are positioned relative to a baseline

  indicating independence (\eqn{d_{ij} = 0}).  If the observed frequency

  of a cell is greater than the expected one, the box rises above the

  baseline and is shaded in the color specified by the first element of

  \code{col}, which defaults to black; otherwise, the box falls below

  the baseline and is shaded in the color specified by the second

  element of \code{col}, which defaults to red.

  A more flexible and extensible implementation of association plots

  written in the grid graphics system is provided in the function

  \code{\link[vcd]{assoc}} in the contributed package \CRANpkg{vcd}

  (Meyer, Zeileis and Hornik, 2005).

}

\seealso{

  \code{\link{mosaicplot}}, \code{\link{chisq.test}}.

}

\references{

  Cohen, A. (1980),

  On the graphical display of the significant components in a two-way

  contingency table.

  \emph{Communications in Statistics---Theory and Methods}, \bold{A9},

  1025--1041.

  Friendly, M. (1992),

  Graphical methods for categorical data.

  \emph{SAS User Group International Conference Proceedings}, \bold{17},

  190--200.

  \url{http://www.math.yorku.ca/SCS/sugi/sugi17-paper.html}

  Meyer, D., Zeileis, A., and Hornik, K. (2005)

  The strucplot framework: Visualizing multi-way contingency tables with vcd.

  \emph{Report 22}, Department of Statistics and Mathematics,

  \enc{Wirtschaftsuniversität}{Wirtschaftsuniversitaet} Wien, Research Report Series.

  \url{http://epub.wu.ac.at/dyn/openURL?id=oai:epub.wu-wien.ac.at:epub-wu-01_8a1}

}

\examples{

## Aggregate over sex:

x <- margin.table(HairEyeColor, c(1, 2))

x

assocplot(x, main = "Relation between hair and eye color")

}

\keyword{hplot}