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R lmer & SAS glimmix
2 messages · Sophie GUERIN, Bert Gunter
It's due to the different coding of contrasts. Post to R-sig-mixed models for a fuller explanation (though it has nothing to do with mixed models; the same would happen with lm) or search on a suitable phrase (e.g. contrast coding in SAS versus R) in R archives or via google etc. -- Bert
On Mon, Nov 12, 2012 at 6:40 AM, Sophie GUERIN <s.guerin at has-sante.fr> wrote:
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 estim?e 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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Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm