# bystats

##### Statistics by Categories

For any number of cross-classification variables, `bystats`

returns a matrix with the sample size, number missing `y`

, and
`fun(non-missing y)`

, with the cross-classifications designated
by rows. Uses Harrell's modification of the `interaction`

function to produce cross-classifications. The default `fun`

is
`mean`

, and if `y`

is binary, the mean is labeled as
`Fraction`

. There is a `print`

method as well as a
`latex`

method for objects created by `bystats`

.
`bystats2`

handles the special case in which there are 2
classifcation variables, and places the first one in rows and the
second in columns. The `print`

method for `bystats2`

uses
the `print.char.matrix`

function to organize statistics
for cells into boxes.

- Keywords
- category

##### Usage

```
bystats(y, …, fun, nmiss, subset)
# S3 method for bystats
print(x, …)
# S3 method for bystats
latex(object, title, caption, rowlabel, …)
bystats2(y, v, h, fun, nmiss, subset)
# S3 method for bystats2
print(x, abbreviate.dimnames=FALSE,
prefix.width=max(nchar(dimnames(x)[[1]])), …)
# S3 method for bystats2
latex(object, title, caption, rowlabel, …)
```

##### Arguments

- y
a binary, logical, or continuous variable or a matrix or data frame of such variables. If

`y`

is a data frame it is converted to a matrix. If`y`

is a data frame or matrix, computations are done on subsets of the rows of`y`

, and you should specify`fun`

so as to be able to operate on the matrix. For matrix`y`

, any column with a missing value causes the entire row to be considered missing, and the row is not passed to`fun`

.- ...
For

`bystats`

, one or more classifcation variables separated by commas. For`print.bystats`

, options passed to`print.default`

such as`digits`

. For`latex.bystats`

, and`latex.bystats2`

, options passed to`latex.default`

such as`digits`

. If you pass`cdec`

to`latex.default`

, keep in mind that the first one or two positions (depending on`nmiss`

) should have zeros since these correspond with frequency counts.- v
vertical variable for

`bystats2`

. Will be converted to`factor`

.- h
horizontal variable for

`bystats2`

. Will be converted to`factor`

.- fun
a function to compute on the non-missing

`y`

for a given subset. You must specify`fun=`

in front of the function name or definition.`fun`

may return a single number or a vector or matrix of any length. Matrix results are rolled out into a vector, with names preserved. When`y`

is a matrix, a common`fun`

is`function(y) apply(y, 2, ff)`

where`ff`

is the name of a function which operates on one column of`y`

.- nmiss
A column containing a count of missing values is included if

`nmiss=TRUE`

or if there is at least one missing value.- subset
a vector of subscripts or logical values indicating the subset of data to analyze

- abbreviate.dimnames
set to

`TRUE`

to abbreviate`dimnames`

in output- prefix.width
- title
`title`

to pass to`latex.default`

. Default is the first word of the character string version of the first calling argument.- caption
caption to pass to

`latex.default`

. Default is the`heading`

attribute from the object produced by`bystats`

.- rowlabel
`rowlabel`

to pass to`latex.default`

. Default is the`byvarnames`

attribute from the object produced by`bystats`

. For`bystats2`

the default is`""`

.- x
an object created by

`bystats`

or`bystats2`

- object
an object created by

`bystats`

or`bystats2`

##### Value

for `bystats`

, a matrix with row names equal to the classification labels and column
names `N, Missing, funlab`

, where `funlab`

is determined from `fun`

.
A row is added to the end with the summary statistics computed
on all observations combined. The class of this matrix is `bystats`

.
For `bystats`

, returns a 3-dimensional array with the last dimension
corresponding to statistics being computed. The class of the array is
`bystats2`

.

##### Side Effects

`latex`

produces a `.tex`

file.

##### See Also

##### Examples

```
# NOT RUN {
bystats(sex==2, county, city)
bystats(death, race)
bystats(death, cut2(age,g=5), race)
bystats(cholesterol, cut2(age,g=4), sex, fun=median)
bystats(cholesterol, sex, fun=quantile)
bystats(cholesterol, sex, fun=function(x)c(Mean=mean(x),Median=median(x)))
latex(bystats(death,race,nmiss=FALSE,subset=sex=="female"), digits=2)
f <- function(y) c(Hazard=sum(y[,2])/sum(y[,1]))
# f() gets the hazard estimate for right-censored data from exponential dist.
bystats(cbind(d.time, death), race, sex, fun=f)
bystats(cbind(pressure, cholesterol), age.decile,
fun=function(y) c(Median.pressure =median(y[,1]),
Median.cholesterol=median(y[,2])))
y <- cbind(pressure, cholesterol)
bystats(y, age.decile,
fun=function(y) apply(y, 2, median)) # same result as last one
bystats(y, age.decile, fun=function(y) apply(y, 2, quantile, c(.25,.75)))
# The last one computes separately the 0.25 and 0.75 quantiles of 2 vars.
latex(bystats2(death, race, sex, fun=table))
# }
```

*Documentation reproduced from package Hmisc, version 4.1-1, License: GPL (>= 2)*