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