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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