note that although PQL is the default method in lmer() for GLMMs, the recent version of the function allow also for Laplace or adaptive Gauss-Hermite approximations. In these cases it might be reasonable to compute AIC values depending on how good the approximation to the likelihood is; however, the use of AIC in mixed models can be tricky depending on the focus of your analysis, check e.g.,
Vaida, F. and Blanchard, S. (2005). Conditional Akaike information for mixed-effects models, Biometrika, 92, 351-370. Regarding inference, I'd rely mainly on LRTs instead of Wald type p-values. I hope it helps. Best, Dimitris ---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/(0)16/336899 Fax: +32/(0)16/337015 Web: http://www.med.kuleuven.be/biostat/ http://www.student.kuleuven.be/~m0390867/dimitris.htm ----- Original Message ----- From: "Elizabeth Boakes" <[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]>; <[email protected]> Sent: Thursday, November 24, 2005 9:53 AM Subject: [R] AIC in lmer when using PQL >I am analysing binomial data using a generalised mixed effects model. >I > understand that if I use glmmPQL it is not appropriate to compare > AIC > values to obtain a minimum adequate model. > > > > I am assuming that this means it is also inappropriate to use AIC > values > from lmer since, when analysing binomial data, lmer also uses PQL > methods. However, I wasn't sure so please could somebody clarify > this > for me. > > > > I was also wondering how best to assess your minimum adequate model > without AIC values? Do you simply have to rely on the p values > associated with the t-values/z-values? > > > > Thanks 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\ > ad...{{dropped}} ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
