R: Score a Series of Binary Variables

score.binary {Hmisc}

R Documentation

Score a Series of Binary Variables

Description

Creates a new variable from a series of logical conditions. The new variable can be a hierarchical category or score derived from considering the rightmost TRUE value among the input variables, an additive point score, a union, or any of several others by specifying a function using the fun argument.

Usage

score.binary(..., fun=max, points=1:p, 
             na.rm=funtext == "max", retfactor=TRUE)

Arguments

`...`	a list of variables or expressions which are considered to be binary or logical
`fun`	a function to compute on each row of the matrix represented by a specific observation of all the variables in `...`
`points`	points to assign to successive elements of `...` . The default is `1, 2, ..., p`, where `p` is the number of elements. If you specify one number for `points`, that number will be duplicated (i.e., equal weights are assumed).
`na.rm`	set to `TRUE` to remove `NA`s from consideration when processing each row of the matrix of variables in `...` . For `fun=max`, `na.rm=TRUE` is the default since `score.binary` assumes that a hierarchical scale is based on available information. Otherwise, `na.rm=FALSE` is assumed. For `fun=mean` you may want to specify `na.rm=TRUE`.
`retfactor`	applies if `fun=max`, in which case `retfactor=TRUE` makes `score.binary` return a `factor` object since a hierarchical scale implies a unique choice.

Value

a factor object if retfactor=TRUE and fun=max or a numeric vector otherwise. Will not contain NAs if na.rm=TRUE unless every variable in a row is NA. If a factor object is returned, it has levels "none" followed by character string versions of the arguments given in ... .

Examples

set.seed(1)
age <- rnorm(25, 70, 15)
previous.disease <- sample(0:1, 25, TRUE)
#Hierarchical scale, highest of 1:age>70  2:previous.disease
score.binary(age>70, previous.disease, retfactor=FALSE)
#Same as above but return factor variable with levels "none" "age>70" 
# "previous.disease"
score.binary(age>70, previous.disease)

#Additive scale with weights 1:age>70  2:previous.disease
score.binary(age>70, previous.disease, fun=sum)
#Additive scale, equal weights
score.binary(age>70, previous.disease, fun=sum, points=c(1,1))
#Same as saying points=1

#Union of variables, to create a new binary variable
score.binary(age>70, previous.disease, fun=any)