lme versus proc mixed in SAS
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