Here's one

MacCallum, Robert C.; Zhang, Shaobo; Preacher, Kristopher J.; Rucker,
Derek D. (2002). On the practice of dichotimization of quantitative
variables. Psychological methods. 7:19-40


HTH

Peter

Peter L. Flom, PhD
Assistant Director, Statistics and Data Analysis Core
Center for Drug Use and HIV Research
National Development and Research Institutes
71 W. 23rd St
www.peterflom.com
New York, NY 10010
(212) 845-4485 (voice)
(917) 438-0894 (fax)



>>> [EMAIL PROTECTED] 3/2/2004 4:33:22 PM >>>
Edstat,

I have personally found that a lot of health researchers like to
aggregate
normally distributed, continuous outcomes into dichotmous outcomes.  In
some
cases, this is done because the researcher is more familiar with
dicohotmous
outcomes (disease/no disease) and seeks to interpret their results in
terms
of odds ratios within a logistic regression.  

In some cases, this can be problematic because you lose information. 
For
instance those near the cut-off point are forced into one group or
another.
Thus, you exaggerate the differences for some individuals.  

If anybody on the listserv can refer me to articles related to this
problem
I would be most appreciative.  Thank you.

Jeff Dang  
.
.
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