[R] lme versus proc mixed in SAS

[Beatrijs Moerkerke]

Dear all,

I am trying to simulate the null distribution for the likelihood ratio 
test statistic for testing 1 random effect versus no random effect.  The 
asymptotic null distribution should be a mixture of a chi-squared 
distribution with 0 degrees of freedom and a chi-squared distribution 
with 1 degree of freedom.  This means that I expect a point mass of 50% 
on 0 for the likelihood ratio test statistic.
However, when I generate data using no random effects and when I 
calculate the test statistics for these data, I never obtain exactly 
zero.  I think this might be due to rounding errors but in fact, 70% of 
the calculated test statistics are negative.  I have compared a few of 
these results with the results in proc MIXED and I found that SAS does 
give test statistics that are exactly zero and gives no negative results.

The code I use for calculating the likelihood ratio test statistics is 
as follows:

a1<-summary(lme(y~x,random=~1|gr,method="ML"))$logLik
a2<-logLik(lm(y~x))
(-2*(a2-a1))

I don't know how I can simulate the null distribution in R using lme.

Thanks for your help,

Kind regards,
Beatrijs Moerkerke

-- 
Beatrijs Moerkerke
Department of Applied Mathematics and Computer Science
Ghent University
Krijgslaan 281 - S9
B-9000 GENT
Tel: +32-(0)9-264.47.56      Fax: +32-(0)9-264.49.95
E-mail: Beatrijs.Moerkerke at UGent.be