Mining for relations between nominal variables

May 1, 2012

(This article was first published on Data and Analysis with R, at Work, and kindly contributed to R-bloggers)

The task today was to find what variables had significant relations with an important grouping variable in the big dataset I’ve been working with lately.  The grouping variable has 3 levels, and represents different behaviours of interest.  At first I tried putting the grouping variable as a dependent variable in a multinomial logistic regression, but I didn’t really trust the output, and the goal was really just to construct a bunch of graphs showing significant bivariate nominal relations in the data..

That’s when I turned to my good old friend, the chi squared test.  All I had to do was select all the variables that I wanted to test against the grouping variable, and construct a list of the chi squared statistic from each test, the variable being tested, and the crosstab of the two variables for later graphing.  So that’s exactly what I did:

One really sweet thing about matrices in R is that you can mix them up with some parts having just numbers, some parts having text, and sub-matrices in other parts!  A typical row of the “resultlist” would look something like this:

xsq    testvar            xtab
[1,]     200.7 “variable1″ numeric,6

Then all I needed to do to see the variable name and crosstab for that variable was to call “resultlist[1,2:3]“, and that gave me the numbers to graph.

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