If you use lmer from the lme4 package (actually it is in the Matrix package but "logically" it is in the lme4 package) to fit a Generalized Linear Mixed Model you have the option of using PQL, or the Laplace approximation or Adaptive Gauss-Hermite Quadrature (AGQ). The log-likelihood for any of these methods, including PQL, is an approximation to the actual log-likelihood of the GLMM model and can be used for likelihood ratio tests.
On 11/30/05, Elizabeth Boakes <[EMAIL PROTECTED]> wrote: > > > I am analysing some binary data with a mixed effects model using > glmmPQL. > > I am aware that I cannot use the AIC values to help me find the minimum > adequate model so how do I perform likelihood ratio tests? I need to > fix on the minimum adequate model but I'm not sure of the proper way to > do this. > > > > Thank you very much, > > Elizabeth Boakes > > Elizabeth Boakes > PhD Student > Institute of Zoology > Regent's Park > London NW1 4RY > tel: 020 7449 6621 > > > > > > _________________________________________________________________________ > This e-mail has been sent in confidence to the named address...{{dropped}} > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html