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 . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
