FactorLevCorr {SSBtools} | R Documentation |
Factor level correlation
Description
A sort of correlation matrix useful to detect (hierarchical) relationships between the levels of factor variables.
Usage
FactorLevCorr(x)
Arguments
x |
Input matrix or data frame containing the variables |
Value
Output is a sort of correlation matrix.
Here we refer to ni as the number of present levels of variable i (the number of unique elements) and we refer to mij as the number of present levels obtained by crossing variable i and variable j (the number unique rows of x[,c(i,j)]).
The diagonal elements of the output matrix contains the number of present levels of each variable (=ni).
The absolute values of off-diagonal elements:
0 |
when mij = ni*nj |
1 |
when mij = max(ni,nj) |
Other values |
Computed as (ni*nj-mij)/(ni*nj-max(ni,nj)) |
So 0 means that all possible level combinations exist in the data and 1 means that the two variables are hierarchically related.
The sign of off-diagonal elements:
positive |
when ni<nj |
negative |
when ni>nj |
In cases where ni=nj elements will be positive above the diagonal and negative below.
Author(s)
Øyvind Langsrud
Examples
x <- rep(c("A","B","C"),3)
y <- rep(c(11,22,11),3)
z <- c(1,1,1,2,2,2,3,3,3)
zy <- paste(z,y,sep="")
m <- cbind(x,y,z,zy)
FactorLevCorr(m)