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

[Stefan Nijssen <stefannijssen@gmail.com>]

Dear,

This is true. The variable AAA AA etc.. is a rating scale, ordered
from AAA to B (in original format this was 1 to represent AAA, 2 to
represent AA etc. until 6 to represent B, from which through "xi
i.Rating, noomit" I created the dummies). I am using the dummies since
for instance the distance between AA and A (2 and 3) might not be the
same as the distance A and BBB (3 and 4). Therefore I don't think the
original variable (with numbers 1 to 6) is the one to read the
correlation from, although this would be easiest.

The reason for my interest in the correlation is that theoretically
the variable Rating is created using variables I use in the regression
in the first place. Any idea how to be able to interpret the
multicorrelation?

Yours,

2011/6/9 Nick Cox <n.j.cox@durham.ac.uk>:
> A correlation coefficient is only likely to have meaning if the combined variable in question is at least on an ordered scale. Even to calculate a meaningless correlation for a six-category scale you would need to have such a combined variable.
>
> Nick
> n.j.cox@durham.ac.uk
>
> Stefan Nijssen
>
> 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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