[EMAIL PROTECTED] (Paul R Swank) wrote in message news:<[EMAIL PROTECTED]>...
Thanks! > What is the nature of the change over time? The nature is a) the treatment (hopefully) and b) the initial change (decrease or increase) after onset of the disease. > If it is linear then a mixed > models analysis looking at change modeled individually for each repsondent > would work. This way, the time between assessments does not have to be the > same across assessments and missing (at random) data can be handled. This > could be done with SAS, SPSS (11), Mlwin, or HLM5 at the least. You mean, calculating the solpes for every subject and the interaction between the two groups? Or are the individually slopes nested under the treatment? Is this the following model? y(ij) = t(i) + x(ij)*b(ij) + e(ij) y(ij): response to timepoint i=2,3,4, subject j t(i): treatment effect x(ij)*b(ij): time x(ij) times slopes b(ij) nested under t May you give me a sample syntax in SPSS for your suggestion? (Problems are most often in details.) Frank Rigous > > Paul R. Swank, Ph.D. > Professor, Developmental Pediatrics > Medical School > UT Health Science Center at Houston > . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
