Posted by
Rich Ulrich on
Mar 16, 2011; 8:24pm
URL: http://spssx-discussion.165.s1.nabble.com/Tau-Kappa-Eta-tp3776719p3798324.html
> Date: Wed, 16 Mar 2011 04:23:23 -0700
> From:
[hidden email]
> Subject: Tau, Kappa, Eta?
> To:
[hidden email]
>[snip]
>
> I doubt which measure for correlation I should use for bivariate
> correlations. Pearson's r is not very suitable as I have only 5 integer
> values in my independent variable and 4 in my dependent variable.
[... snip]
Use Pearson's r. Yes, it shows effects of "attenuation", especially
between variables that are dichotomies. Other than for dichotomies, the
attenuation is pretty negligible. And you don't have dichotomies.
People are accustomed to Pearson's r. Its size has implications
that are better known to everyone, statisticians or other readers,
than any other correlations.
Where do you get that notion, that the Pearson's is not suitable?
- A Pearson is a good estimate of a weighted kappa.
- An intra-class correlation is the useful generalization for
multiple raters, if you can't be better satisfied by looking at
pair-wise Pearson's.
One proper way to avoid problems with high inter-correlations among
a set of predictors is to compute one or more composite scores to use
as predictors instead.
--
Rich Ulrich
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