xtabs {base}R Documentation

Cross Tabulation

Description

Create a contingency table from cross-classifying factors, usually contained in a data frame, using a formula interface.

Usage

xtabs(formula = ~., data, subset, na.action, exclude = c(NA, NaN),
      drop.unused.levels = FALSE)
summary.xtabs(object, ...)

Arguments

formula a formula object with the cross-classifying variables, separated by +, 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 beed tabulated, see the examples below.
data a data frame, list or environment containing the variables to be cross-tabulated.
subset an optional vector specifying a subset of observations to be used.
na.action a function which indicates what should happen when the data contain NAs.
exclude a vector of values to be excluded when forming the set of levels of the classifying factors.
drop.unused.levels a logical indicating whether to drop unused levels in the classifying factors. If this is 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.

Details

There is a summary method for contingency table objects created by xtabs, which currently gives basic information and performs a chi-squared test for independence of factors (note that the function chisq.test in package ctest currently only handles 2-d tables).

Value

A contingency table in array representation of class "xtabs", with a "call" attribute storing the matched call.

See Also

table for ``traditional'' cross-tabulation, and as.data.frame.table which is the inverse operation of xtabs (see the DF example below).

Examples

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))