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: [EMAIL PROTECTED]
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