Dear all,
I am fitting a logistic model :
glm(y ~ agecl*period + size + gradecl, ...)
where:
agecl =0 for "aged 50-59", =1 for "aged 60-69", =2 for "aged 70 +"
period =0 for "1990-92", =1 for "1993-95", =3 for "1996-98"
size is in a continuous form (from 1 to ...)
gradecl =0 for "Grade1", =1 for "Grade2", =2 for "Grade3"
Question :
The interaction terme is significant. I would like to get estimate for all the
effects, mainly concerning agecl*period and then to plot the "agecl" effect
according to the "period".
I think that I have to use the predict.glm function and have to create a
newdata containing all the predictors. Given that my focus is on agecl*period
what values I have to put in these newdata for size and gradecl?
Am I wrong?
Thanks for any comments and help for a computational solution.
Yours
Roch
_____________________________________________________
Roch GIORGI, MD, PhD
Service de Santé Publique et d'Information Médicale
Hôpital de la Timone
264, rue St Pierre
13385 Marseille cedex 5
Tel: +33 (0)491 384 949
Fax: +33 (0)491 385 749
email: roch.giorgi@ap-hm.fr
Web: http://cybertim.timone.univ-mrs.fr/
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