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 (or an object which
can be coerced to a formula). 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 have already been tabulated, see the examples below. |

`data` |
an optional matrix or data frame (or similar: see
`model.frame` ) containing the variables in the
formula `formula` . By default the variables are taken from
`environment(formula)` . |

`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. |

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))

[Package *stats* version 2.5.0 Index]