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- From: rons@hardy.u.washington.edu (Ronald Schoenberg)
- Subject: Re: Binary Correlations. Was: Levels of Measurement?
- Message-ID: <1992Dec17.203637.8119@u.washington.edu>
- Sender: news@u.washington.edu (USENET News System)
- Organization: University of Washington, Seattle
- References: <92351.201518U53076@uicvm.uic.edu> <thompson.724607838@daphne.socsci.umn.edu>
- Date: Thu, 17 Dec 1992 20:36:37 GMT
- Lines: 30
-
- In article <thompson.724607838@daphne.socsci.umn.edu> thompson@atlas.socsci.umn.edu writes:
- >Perhaps someone interested in the levels of measurement question might
- >be able to help me too.
- >
- >I have been acting as informal statistical consultant for my wife, who
- >is a physician with only an elementary statistical background, in a
- >project where she wants measures of association between a fairly large
- >number of binary variables in a sample with n=500 and in a subsample
- >with n = 260. (These numbers may increase in the future.)
- >
- >We have been calculating standard Pearson correlation coefficients,
- >which to my way of thinking are as good as anything else at describing
- >binary associations, since scaling is not an issue for binary data. I
- >
- [....]
- >
- >If you were in my shoes would you stick with the Pearson correlations
- >or do something different? If the latter, would you provide a
- >reference please.
- >
- >Related and more interesting question:
- >
- >What is "the right way" to do this from the point of view of
- >statistical theory?
- >--
-
- I would compute polychoric coefficients - conceptually they are
- correlations of latent normal variables for which below a threshold we
- observe the case being in one category and above we observe it in
- another category.
-