I have a sample of ~120 subjects assessed 3 times (longitudinally) for
depression severity. I'm analyzing change in depression scores via GEE with the GENLIN procedure. However, subjects come from 5 distinct villages, and I want to adjust for any clustering effect of village. My understanding is that to do the latter, I need to use one of the procedures in the Complex Samples add-on, such as the CSGLM procedure. In other words, GENLIN seems designed to take care of correlation among measures WITHIN a subject, while the correlation corrected for in CSGLM or the other Complex Samples procedures seems to be correlation BETWEEN subjects belonging to different clusters (e.g., villages, school, families). I'm unaware of a way to accomplish both my goals using ONE procedure. Perhaps I could do the GEE analysis and then do a separate analysis to estimate the design effect from sampling distinct villages, and then somehow apply the design effect to the GEE results (perhaps manually) to "correct" the standard errors from the GEE output? Does anybody have any advice? Thanks in advance! ===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD |
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Hi Marc. Have you considered a multilevel model (via MIXED or the newer procedure in v19) with Level 1 = Occasion, Level 2 = Subject, and Level 3 = village?
HTH.
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