<[EMAIL PROTECTED]> writes: > Three related questions on LMEs and GLMMs in R: > > (1) Is there a way to fix the dispersion parameter (at 1) in either > glmmPQL (MASS) or GLMM (lme4)? > > Note: lme does not let you fix any variances in advance (presumably > because it wants to "profile out" an overall sigma^2 parameter) and > glmmPQL repeatedly calls lme, so I couldn't see how glmmPQL would be > able to fix the dispersion parameter. The section on glmmPQL in V&R4 > says that the default is to estimate the dispersion parameter, but > didn't seem to say how to change the default.
At the core of the lme calculations is the solution of a penalized least squares problem defined by the relative dispersion matrix of the random effects and the model matrices for the random effects and the fixed effects. In versions 0.6-1 and later of the lme4 package (the first release candidate is available from my web site http://www.stat.wisc.edu/~bates/) the components of the log-likelihood or the REML criterion are available as the devComp slot of the S4 object that represents the model and that is used to solve the penalized least squares problem. If, using these components, you can write the log-likelihood for the model that you wish to fit then you can give it to an optimizer such as optim or nlm to fit. In the notation of Bates and DebRoy (2004), "Linear mixed models and penalized least squares" (to appear in J. of Multivariate Analysis, available in preprint form from my web site), the components are log(|Z'Z + \Omega|), log(|\Omega|), log(|R_{XX}|^2), and log(r_{yy}^2) The C code that uses these to evaluate the deviance form of the profiled log-likelihood criterion or the profiled REML criterion from these components is in src/ssclme.c from the Matrix package. Modifying the criteria for a fixed dispersion parameter may be trivial or it may not. > (3) Are there any plans to allow some variances to be fixed in lme? > It would be useful e.g. for meta-analysis (and indeed for glmms with > fixed dispersion). The method = 'Laplacian' version of the GLMM function fixes the dispersion parameter in those families where it should be fixed. As we continue to develop lme4 we will provide a further enhancement using an adaptive Gauss-Hermite evalution of the log-likelihood for GLMMs that will also have this property. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
