[R] glmmPQL and variance structure

[Spencer Graves]

	  Have you received a reply to this post?  I haven't seen one.  I don't 
have an answer for you, but if you'd still like help from this list, I 
suggest you prepare the simplest possible toy example that you can 
conceive and send it to this list, restating your question in terms of 
that example.  You question indicates you've read the code for glmmPQL 
and seem to know enough to experiment with modifying the "glmmPQL" code 
or with extracting crucial pieces to make part of the simplified example 
illustrating your question (consistent with the posting guide, 
"www.R-project.org/posting-guide.html").

	  If you are not sure what "glmmPQL" does, you can say "debug(glmmPQL)" 
before executing a command that invokes "glmmPQL".  That will open a 
browser that will allow you to look at and change anything in the 
environment of "glmmPQL" before and after any command;  if a command 
commits a fatal error, you will be evicted from "glmmPQL" and will have 
to start over.  This is the quickest way I know to understand and debug 
R code.

	  hope this helps.
	  spencer graves

Patrick Giraudoux wrote:

> Dear listers,
> 
> glmmPQL (package MASS) is given to work by repeated call to lme. In the 
> classical outputs glmmPQL  the Variance Structure is given  as " fixed 
> weights,  Formula: ~invwt".  The script shows that the function 
> varFixed() is used, though the place where 'invwt' is defined remains 
> unclear to me.  I wonder if there is an easy way to specify another 
> variance structure (eg varPower, etc..), preferably using an lme object 
> of the varFunc classes ? Some trials show that the 'weights' argument of 
> glmmPQL is just the same as in glm (which is clearly stated in the help) 
> and I wonder actually, if not a nonsense, how to pass eg a 'weights' 
> arguments as used in lme (eg weights=varPower()) to specify a variance 
> function (in the same way as a correlation structure can be passed easy).
> 
> Thanks in advance for any hint,
> 
> Patrick
> 
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-- 
Spencer Graves, PhD
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