Date: Sun, 30 Mar 2008 12:24:21 -0700
Reply-To: Pierre Nouvellet <pierrenouvellet@HOTMAIL.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: Pierre Nouvellet <pierrenouvellet@HOTMAIL.COM>
Subject: mixed model + generalized linear model
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Hi, I'm no expert on stats, and i have found a bit of a challenge
I was first trying to deal with it with SPSS, but I've been advised to
use either SAS or R
I understand the 2 languages are rather similar...
I have 4 variables:
Ra: count, number of road traffic accident involving an animal
T: temperature for the month
my data are in long format.
i want to test: Ra~Y+M+M*T .
more specifically i want to know if monthly temperature influence the
monthly count, and if so which month have a significant impact (slope
different from 0!).
since each year a different effort is put to record the accident I
need to include it. also I am happy to assume that in reality the
count should be the same each year... So I just want to correct the
since each month may have different count i include it too.
what i really want is to know the SLOPES of the relation for each
month (controling for effect of year and month) and if it is
significantly different from zero!
I understand year should be taken as random factor? (1) (I am not
interested in knowing the influence of year, since I assume the
variation only due to effort).
and if you use random factor, better to include them in a mixed
As fixed factor, I include M and interaction M*T (2) ,
As random factor, I include year, any tips on covariance type and
contrast I should use?(3)
so it is really 3 question in one... As well as have some input to
wether the choice of model is appropriate...
thanks for taking the time....