Using R to run multilevel models

I'm learning how to run multilevel models in R.

I tried the analysis of variance model, AKA, the intercept-only model.

fit<lme(post_test~1,random=~1|school,data=mySASData,control=list(opt="optim"))
summary(fit)
anova(fit)
VarCorr(fit)
summary(fit)

 

I run this in SAS and get the same results.  I didn't get the same degree of freedom.

proc glimmix data=sashlm.core_2014_4_years;
class school;
model post_test=/solution ddfm=kr dist=normal link=identity;
random intercept /subject=school;
run;

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