R: Cross Tabulation

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 = parent.frame(), subset, na.action,
          exclude = c(NA, NaN), drop.unused.levels = FALSE)

### 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 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 `NA`s.
`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 `table` or `xtabs`, which 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).

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.

### Value

A contingency table in array representation of class `c("xtabs", "table")`, 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))

    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))

[Package Contents]