🚀 go-pugleaf

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
do not claim to have studied the issue in depth, however.

I am an econometrician and I know that different fields have different
statistical subcultures and norms, so I am not sure that this is what
other physicians, biostatisticians, epidemiologists, etc. expect.  My
impression is that medicine is the field where statistical practice is
most codified, meaning that there are conventions that must be
satisfied if you want to get published, even if they don't make a
whole lot of sense in the particular application.

So here is my question:

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?
--
T. Scott Thompson              email:  thompson@atlas.socsci.umn.edu
Department of Economics        phone:  (612) 625-0119
University of Minnesota        fax:    (612) 624-0209