On Thu, 13 May 2004 [EMAIL PROTECTED] wrote: > 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)?
not glmmPQL in R (can be done in S-PLUS). > 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. It's done in the same way as for lme via the control parameter (that is, not at all in R). > (2) Is there a way to tell lme (either in nlme or lme4) to just use a > specified design matrix Z for the random effects, rather than > constructing one itself from factors? Sometimes I would really like to > use my own funny-looking Z matrix (e.g. with non-integer coefficients), > and even with contrasts() I haven't managed to do this. > > (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). It has been possible for a while in S-PLUS. > Note: it has occurred to me that lme can possibly be tricked into fixing > the measurement error variance (i.e. var[y|b] where b is the random > effects and y the observed data) at some specified value e.g. 1 by > adding two pseudo-observations at +/-1, with all zeros in the > corresponding rows of the X and Z matrices, and with huge weights. Then > sum( w*(y-E[y|b,params])^2) / sum(w) will be approximately 1, and any > attempt to change the estimate of sigma^2 away from 1 will be "deterred" > by a large penalty. Similar tricks might be possible for fixing other > variances. However this approach is not nice and perhaps might cause > computational problems-- and I haven't actually tried it yet. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [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
