brkdnNest: Perform a nested breakdown of numeric values

In plotrix: Various Plotting Functions

Perform a nested breakdown of numeric values

Description

Breaks down a numeric or categorical element of a data frame by one or more categorical elements.

Usage

 brkdnNest(formula,data,FUN=c("mean","sd","sd","valid.n"),label1="Overall",
  trueval=TRUE)

Arguments

formula	A formula with a numeric element of a data frame on the left and one or more categorical elements on the right.
data	A data frame containing the elements in ‘⁠formula⁠’.
FUN	The functions to be applied to successive breakdowns.
label1	The label to use for the overall value of the first function.
trueval	The value to use in calculating proportions or sums of a categorical response variable. See Details.

Details

‘⁠brkdnNest⁠’ performs a nested breakdown of an element of a data frame by one or more categorical elements. For each category and optional subcategories, the variable on the left of the formula is summarized as specified by the functions named in ‘⁠FUN⁠’.

If ‘⁠trueval⁠’ is not NA, brkdnNest will calculate the proportion of ‘⁠trueval⁠’ values in the response variable out of the total valid responses. If the function ‘⁠valid.n⁠’ is the first function in ‘⁠FUN⁠’, the counts of the groups and subgroups will be returned.

Two specialized summary functions are defined within ‘⁠brkdnNest⁠’. ‘⁠sumbrk⁠’ returns the count of values in a factor equal to ‘⁠trueval⁠’, and ‘⁠propbrk⁠’ returns the proportion of values equal to ‘⁠trueval⁠’. Be aware that if a categorical variable is specified on the left of the formula, functions which expect numeric data such as ‘⁠mean⁠’ should not be included in ‘⁠FUN⁠’.

The user should take care when specifying different summary functions. ‘⁠barNest⁠’ expects a summary measure as the first component of the list and measures of dispersion as the second and third. If two different measures of dispersion are passed, the first must calculate the upper and the second the lower measure.

Value

A list with as many elements as there are functions in ‘⁠FUN⁠’. It is probably best to always specify four functions (summary measure, upper dispersion measure, lower dispersion measure and number of valid observations) even if this is redundant as in the default.

This function is similar to ‘⁠brkdn⁠’ in the prettyR package, but is structured to be used with the ‘⁠barNest⁠’ function. It produces one or more measures for the overall data, then the subsets of the data defined by the first variable to the right of the tilde, then the subsets defined by the first and second variable, and so on.

Author(s)

Jim Lemon

See Also

by

Examples

 brkdntest<-data.frame(Age=rnorm(100,25,10),
  Sex=factor(sample(c("M","F"),100,TRUE)),
  Marital=sample(c("M","X","S","W"),100,TRUE),
  Employ=sample(c("FT","PT","NO"),100,TRUE))
 brkdnNest(formula=Age~Sex+Marital+Employ,data=brkdntest)
 # show the proportion of unemployed with binomial confidence intervals
 brkdnNest(formula=Employ~Sex+Marital,data=brkdntest,
  FUN=c("propbrk","binciWu","binciWl"),trueval="NO")

plotrix documentation built on Nov. 10, 2023, 5:07 p.m.