Pseudo-function to compute a statistic relative to a reference set.
Percent.RdThe 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 115 49.15 119 50.85 234 100
#> d 142 55.04 116 44.96 258 100
#> All 257 52.24 235 47.76 492 100
#> B c 132 51.16 126 48.84 258 100
#> d 126 50.40 124 49.60 250 100
#> All 258 50.79 250 49.21 508 100
#> All c 247 50.20 245 49.80 492 100
#> d 268 52.76 240 47.24 508 100
#> All 515 51.50 485 48.50 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 115 49.15 119 50.85 234 100
#> d 142 55.04 116 44.96 258 100
#> All 257 52.24 235 47.76 492 100
#> B c 132 51.16 126 48.84 258 100
#> d 126 50.40 124 49.60 250 100
#> All 258 50.79 250 49.21 508 100
#> All c 247 50.20 245 49.80 492 100
#> d 268 52.76 240 47.24 508 100
#> All 515 51.50 485 48.50 1000 100