[R] association of multiple variables

[David Carlson]

You might modify this function which computes Cramer's V using
the assocstats() function in package vcd:

catcor <- function(x) {
	require(vcd)
	nc <- ncol(x)
	v <- expand.grid(1:nc, 1:nc)
	matrix(mapply(function(i1, i2) assocstats(table(x[,i1], 
		x[,i2]))$cramer, v[,1], v[,2]), nc, nc)
}

e.g.

> dat <- data.frame(v1=sample(LETTERS[1:5], 15, replace=TRUE), 
+ v2=sample(LETTERS[1:5], 15, replace=TRUE),
+ v3=sample(LETTERS[1:5], 15, replace=TRUE))
> catcor(dat)
          [,1]      [,2]      [,3]
[1,] 1.0000000 0.5633481 0.5773503
[2,] 0.5633481 1.0000000 0.6831301
[3,] 0.5773503 0.6831301 1.0000000

-------------------------------------
David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: r-help-bounces at r-project.org
[mailto:r-help-bounces at r-project.org] On Behalf Of Skála, Zdenek
(INCOMA GfK)
Sent: Tuesday, February 18, 2014 3:33 AM
To: r-help at r-project.org
Subject: [R] association of multiple variables

Dear all,

Please, is there a way in R to calculate association statistics
over more than 2 categorical (binary) variables?
I mean something similar what

cor(my.dataframe)

does for continuous variables, i.e. to have a matrix of
statistics and/or p-values as an output.

Many thanks!

Zdenek

- -
Zdenlk Skala
INCOMA GfK

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