```Date: Fri, 2 Jan 2004 12:24:48 -0800 Reply-To: David Reilly Sender: "SAS(r) Discussion" From: David Reilly Organization: http://groups.google.com Subject: Re: Test for Trend: SAS Content-Type: text/plain; charset=ISO-8859-1 findingjobs@hotmail.com (Sharon) wrote in message news:<634180b6.0312060429.791a26a@posting.google.com>... > Hi there, two questions. I'm using SAS for my analysis. > > QUESTION ONE: I'm using generalized estimating equations (GEE) for my > analysis and one of my variables has an obvious decrease in trend. Is > there a way to do a "test for trend" using PROC GENMOD? > > QUESTION TWO: In the absence of GEE, I'd like to assume independence, > just to get a sense of the trend (I know this is inappropriate, given > the correlated data). I know I can use PROC FREQ to do a "test for > trend" for unadjusted odds ratios but is there a way i can calculate > "test for trend" for ADJUSTED odds ratios? > > Thanks in advance! Sharon, Tests for the difference in "TRENDS" between two time series require that there is a common KIND OF TREND. For example y(t)=y(t-1) + CONSTANT1 is one form of a TREND MODEL a second example y(t)= CONSTANT2 + CONSTANT3*TIME is another form of a TREND MODEL a third example y(t)= CONSTANT4 + CONSTANT5*x(t) is yet another form of a TREND MODEL . Now let's assume that you have no causals (x's ) thus your problem is to determine which of the first two TREND MODELS is appropriate. To complicate matters consider the first kind of TREND y(t)= y(t-1) + CONSTANT1 if t => to otherwise y(t)= y(t-1) + CONSTANT2 thus the TREND depends on where you are in time. Additionally consider models of the second kind where y(t)= CONSTANT2 + CONSTANT3*TIME if t => to otherwise y(t)= CONSTANT2 In order to test for a common trend one needs a common model form across the two groups otherwise there is a de facto difference. If one can assume a common model form then one estimates globally and locally and performs an F Test on the differential SOS in order to test the hypothesis of a COMMON TREND . Hope this helps. Dave Reilly Automatic Forecasting Systems http://www.autobox.com ```

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