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st: RE: creating combined correlation of dummy (ordered multilevel)


From   "Jacobs, David" <[email protected]>
To   "'[email protected]'" <[email protected]>
Subject   st: RE: creating combined correlation of dummy (ordered multilevel)
Date   Thu, 9 Jun 2011 17:32:01 +0000

Perhaps I'm not understanding something, but you seem to want the equivalent of a correlation between some underlying dimension represented by your dummy variables and other (continuous?) variables. 

If this is correct, why not regress each of the other variables on the dummies.  Then look as the square root of the multiple R2 to obtain the overall relationship as represented by the multiple R.

Dave Jacobs

-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Stefan Nijssen
Sent: Thursday, June 09, 2011 10:46 AM
To: [email protected]
Subject: st: creating combined correlation of dummy (ordered multilevel)

Dear Statalist members,

I am struggling to find the correlation of various variables to a dummy variable (6level ordered). The problem is that since the dummies appear in the table as six variables, I cannot read a single correlation between the combined dummy and any other variable (see below). Does anyone know how to do this?

Stefan Nijssen

. correlate AAA AA A BBB BB B wc5 MAR COV
(obs=383)

             |      AAA       AA        A      BBB       BB        B      wc5      MAR      COV
-------------+---------------------------------------------------------------------------------
         AAA |   1.0000
          AA |  -0.0303   1.0000
           A |  -0.0767  -0.1249   1.0000
         BBB |  -0.1187  -0.1932  -0.4892   1.0000
          BB |  -0.0559  -0.0909  -0.2302  -0.3563   1.0000
           B |  -0.0504  -0.0820  -0.2077  -0.3214  -0.1513   1.0000
         wc5 |   0.3377   0.1016   0.1805  -0.1683  -0.0769  -0.1032   1.0000
         MAR |   0.0030   0.0101   0.0146   0.0449  -0.0136  -0.0807   0.0176   1.0000
         COV |   0.3052   0.1377   0.2432  -0.0967  -0.1235  -0.2545   0.2121   0.1220   1.0000




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