| xtabs {stats} | R Documentation |
Create a contingency table from cross-classifying factors, usually contained in a data frame, using a formula interface.
xtabs(formula = ~., data = parent.frame(), subset, na.action,
exclude = c(NA, NaN), drop.unused.levels = FALSE)
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 been 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. |
There is a summary method for contingency table objects created
by table or xtabs, which gives basic information and
performs a chi-squared test for independence of factors (note that the
function chisq.test currently only handles 2-d tables).
If a left hand side is given in 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.
A contingency table in array representation of class c("xtabs",
"table"), with a "call" attribute storing the matched call.
table for “traditional” cross-tabulation, and
as.data.frame.table which is the inverse operation of
xtabs (see the DF example below).
## '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)) ## 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 independence ... summary(xtabs(Freq ~ ., DF)) ## Create a nice display for the warp break data. warpbreaks$replicate <- rep(1:9, len = 54) ftable(xtabs(breaks ~ wool + tension + replicate, data = warpbreaks))