\Header{xtabs}{Cross Tabulation}
\alias{print.xtabs}{xtabs}
\keyword{category}{xtabs}
\begin{Description}\relax
Create a contingency table from cross-classifying factors, usually
contained in a data frame, using a formula interface.\end{Description}
\begin{Usage}
\begin{verbatim}
xtabs(formula = ~., data = parent.frame(), subset, na.action,
      exclude = c(NA, NaN), drop.unused.levels = FALSE)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{formula}] a formula object with the cross-classifying variables,
separated by \code{+}, on the right hand side.  Interactions are not
allowed.  On the left hand side, one may optionally give a vector or
a matrix of counts; in the latter case, the columns are interpreted
as corresponding to the levels of a variable.  This is useful if the
data has already been tabulated, see the examples below.
\item[\code{data}] a data frame, list or environment containing the variables
to be cross-tabulated.
\item[\code{subset}] an optional vector specifying a subset of observations
to be used.
\item[\code{na.action}] a function which indicates what should happen when
the data contain \code{NA}s.
\item[\code{exclude}] a vector of values to be excluded when forming the
set of levels of the classifying factors.
\item[\code{drop.unused.levels}] a logical indicating whether to drop unused
levels in the classifying factors.  If this is \code{FALSE} and
there are unused levels, the table will contain zero marginals, and
a subsequent chi-squared test for independence of the factors will
not work.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
There is a \code{summary} method for contingency table objects created
by \code{table} or \code{xtabs}, which gives basic information and
performs a chi-squared test for independence of factors (note that the
function \code{\Link{chisq.test}} in package \bold{ctest}
currently only handles 2-d tables).

If a left hand side is given in \code{formula}, its entries are simply
summed over the cells corresponding to the right hand side; this also
works if the lhs does not give counts.\end{Details}
\begin{Value}
A contingency table in array representation of class \code{c("xtabs",
    "table")}, with a \code{"call"} attribute storing the matched call.\end{Value}
\begin{SeeAlso}\relax
\code{\Link{table}} for ``traditional'' cross-tabulation, and
\code{\Link{as.data.frame.table}} which is the inverse operation of
\code{xtabs} (see the \code{DF} example below).\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(esoph)
## `esoph' has the frequencies of cases and controls for all levels of
## the variables `agegp', `alcgp', and `tobgp'.
xtabs(cbind(ncases, ncontrols) ~ ., data = esoph)
## Output is not really helpful ... flat tables are better:
ftable(xtabs(cbind(ncases, ncontrols) ~ ., data = esoph))
## In particular if we have fewer factors ...
ftable(xtabs(cbind(ncases, ncontrols) ~ agegp, data = esoph))

data(UCBAdmissions)
## This is already a contingency table in array form.
DF <- as.data.frame(UCBAdmissions)
## Now `DF' is a data frame with a grid of the factors and the counts
## in variable `Freq'.
DF
## Nice for taking margins ...
xtabs(Freq ~ Gender + Admit, DF)
## And for testing independece ...
summary(xtabs(Freq ~ ., DF))

data(warpbreaks)
## Create a nice display for the warp break data.
warpbreaks$replicate <- rep(1:9, len = 54)
ftable(xtabs(breaks ~ wool + tension + replicate, data = warpbreaks))
\end{ExampleCode}
\end{Examples}

