# Pseudo-function to compute a statistic relative to a reference set.

`Percent.Rd`

The `Percent`

pseudo-function is used to specify
a statistic that depends on other values in the table.

## Details

The function `fn`

will be called with two
arguments. The first argument is the usual “value vector”
of values
corresponding to this cell in the table,
and the second
is another vector of reference values, determined
by `denom`

.

The default value of `fn`

is the `percent`

function,
defined as `function(x, y) 100*length(x)/length(y)`

. This
gives the ratio of the number of values in the current cell
relative to the reference values, expressed as a percentage.
Using `fn = function(x, y) 100*sum(x)/sum(y)`

would give
the percentage of the sum of the values in the current cell to
the sum in the reference set.

With the default `denom = "all"`

, all values of the
analysis variable in the dataset are used as the reference. Other possibilities
are `denom = "row"`

or `denom = "col"`

, for which
the values of the variable corresponding to the current row
or column subset are used.

The special syntax `denom = Equal(...)`

will record
each expression in `...`

. The
reference set will be the cases with equal values of all
expressions in `...`

to those of the current cell.
The similar form `denom = Unequal(...)`

sets the reference values to be those that differ in any
of the `...`

expressions from the current cell. (In
fact, these can be used somewhat more generally; see the
vignette for details.)

Finally, other possible `denom`

values
are a logical vector, in which
case the values marked `TRUE`

are used, or anything else, which will
be passed to `fn`

as `y`

without any subsetting. (To pass a variable with subsetting,
use the `Arguments`

pseudo-function instead.)

## Pseudo-functions

`Percent`

is a “pseudo-function”: it takes the form of a function call, but is
never actually called: it is
handled specially by `tabular`

. `Equal`

and `Unequal`

are also pseudo-functions, but are only special when used
in the `denom`

argument to `Percent`

.

## See also

`Arguments`

for a different way to specify
a multiple argument analysis function.

## Examples

```
x <- factor(sample(LETTERS[1:2], 1000, replace = TRUE))
y <- factor(sample(letters[3:4], 1000, replace = TRUE))
z <- factor(sample(LETTERS[5:6], 1000, replace = TRUE))
# These both do the same thing:
tabular( (x + 1)*(y + 1) ~ (z + 1)*(1+(RowPct=Percent("row"))))
#>
#> z
#> E F All
#> x y All RowPct All RowPct All RowPct
#> A c 118 50.64 115 49.36 233 100
#> d 139 54.30 117 45.70 256 100
#> All 257 52.56 232 47.44 489 100
#> B c 132 50.77 128 49.23 260 100
#> d 127 50.60 124 49.40 251 100
#> All 259 50.68 252 49.32 511 100
#> All c 250 50.71 243 49.29 493 100
#> d 266 52.47 241 47.53 507 100
#> All 516 51.60 484 48.40 1000 100
tabular( (x + 1)*(y + 1) ~ (z + 1)*(1+(xyPct=Percent(Equal(x, y)))))
#>
#> z
#> E F All
#> x y All xyPct All xyPct All xyPct
#> A c 118 50.64 115 49.36 233 100
#> d 139 54.30 117 45.70 256 100
#> All 257 52.56 232 47.44 489 100
#> B c 132 50.77 128 49.23 260 100
#> d 127 50.60 124 49.40 251 100
#> All 259 50.68 252 49.32 511 100
#> All c 250 50.71 243 49.29 493 100
#> d 266 52.47 241 47.53 507 100
#> All 516 51.60 484 48.40 1000 100
```