a formula object with the terms, separated by +
operators, on the right of the ~. Each term on the right
hand side should be a factor, and will be converted to one
if not. If there is a term to the left of the ~ it should
be a vector of counts -- this useful for data that has al-
ready been tabulated. If the formula is omitted or is ~ .
and the data argument is a data frame, then all the
variables in data will be crosstabulated.
OPTIONAL ARGUMENTS:
data
a data frame or frame number telling where the variables
named in the formula (and in the subset argument) may be
found. If a variable is not found by searching in the
data frame or frame given by data, it is expected to be on
the search list.
subset
an expression telling which subset of the rows of the data
should be used in the table. It can be an expression that
evaluates to a logical vector, or a vector of logical
values, or a vector of row numbers or row names---in
short, anything you would normaly use to subscript the
rows of a data frame. The variable names in the
expression should be names in the same place supplied by the
data argument, otherwise they will be looked for on the
search list. All observations are included by default.
na.action
a function for handling missing values. If there
are any missing values in the data to be crosstabulated,
the data will be put into a data frame and passed to the
function given by na.action. The default is na.fail,
which issues a fatal error message describing the problem.
A common alternative is
na.omit, which deletes cases with
NAs in any of the variables to be crosstabulated.
na.include will add the level
NA to each factor
before crosstabulating them
(
formula may also include terms like
na.include(x)
to do this only for certain variables).
drop.unused.levels
if
TRUE, then any unused levels in factors will be omitted from the table.
If
FALSE, they will not be dropped and the table will contain rows or
columns of zeros for those unused levels.
This will cause the marginal proportions for those levels and the overall
chi-squared statistic to be
NAs,
but may be useful for making parallel tables of similar data sets.
print.object.p
if
TRUE, a contingency table is printed.
This output is from the function
print.crosstabs.
margin.p
if
TRUE, print marginal total.
digits
number of digits after the decimal point to use when
displaying the proportions in the crosstabs tables.
marginal.totals
if
TRUE (the default if the table has more than one dimension),
print the row and column totals for each two dimensional layer of the table
along side the layer.
Also print the layer total and the proportion each row and column
is of the layer total.
chi2.test
if
TRUE,
(the default if the table has more than one dimension),
print the result of the chi-square test for independence
of all the variables in the table.
Yates' correction is not used.
VALUE:
an object of class
"crosstabs".
This is an array of counts.
It also has an attribute marginals,
a list of arrays of the marginal proportions.
(These arrays are stacked by the print method for crosstabs so that
corresponding entries lie near each other.)
It also may have an attribute
na.message,
giving a message that the
na.action function sometimes gives
when it deals with missing values in the data
(e.g.,
na.omit will supply a
na.message
telling how many cases were ignored).