Hi,
I am trying to fit a model with lmer in R and proc glimmix in SAS. I have
simplified my code but I am surprised to see I get different results from
the two softwares.
My R code is :
lmer(y~age_cat + (1|cat),data=fic,family=binomial(link = "logit"), NaGQ=1)
My SAS code is :
ods output Glimmix.Glimmix.ParameterEstimates=t_estimates;
proc glimmix data=tab_psi method=laplace;
class age_cat cat;
model psi (event='1') = age_cat / solution dist=B link=logit ;
random intercept / subject=cat;
run;
>From R, I get the following fixed effects
(Intercept) age_cat2. 76-85 ans age_cat3. 66-75 ans age_cat4. 41-65 ans
-3.5766898 -0.0159466 -0.1919500 -0.4834741
age_cat5. 18-40 ans
-1.2843977
But from SAS I get :
Valeur Erreur Valeur
Effet age_cat estimée type DDL du
test t Pr > |t|
Intercept -4.8608 0.2859 3 -17.00
0.0004
age_cat 1. >85-108 a 1.2841 0.2589 168E3 4.96
<.0001
age_cat 2. 76-85 ans 1.2681 0.2528 168E3 5.02
<.0001
age_cat 3. 66-75 ans 1.0921 0.2529 168E3 4.32
<.0001
age_cat 4. 41-65 ans 0.8006 0.2535 168E3 3.16
0.0016
age_cat 5. 18-40 ans 0 . . .
.
Even the intercept is different, but I can't find why. Has anyone an idea?
Thanks in advance,
Sophie
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