[Note: The original post should have been to sci.stat.consult, not sci.stat.edu]
Categorizing continuous variables to avoid a linearity assumption is always a curious thing to do in my view. Is a piecewise flat relationship more realistic than a linear one? Regression splines and other flexible approaches do away with the need for the linearity assumption anyway. Frank Harrell On 17 Apr 2002 15:32:27 -0700 [EMAIL PROTECTED] (wuzzy) wrote: > How do you dichotomize a continuous variable, like age, into 3 decades > of life. > And is this a good thing to do in linear regression? > > Is it just > > V1: ages0-10=1 else =0 > V2: ages11-20=1 else =0 > v3: ages21-30=1 else =0 > > and then plug it in as outcome = v1 + v2 + v3 (where outcome is > continuous). > > > I want to do this because I think this would reduce my variation > within groups,(measurement error) also I think that the effect of the > different decades is not linear within the groups. -- Frank E Harrell Jr Prof. of Biostatistics & Statistics Div. of Biostatistics & Epidem. Dept. of Health Evaluation Sciences U. Virginia School of Medicine http://hesweb1.med.virginia.edu/biostat . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
