[R] Mixed model question

[ronggui]

and the newest R-new in the www.r-project.org has an article about how to use the lmer function.

On Fri, 17 Jun 2005 08:43:41 -0700
Spencer Graves <spencer.graves at pdf.com> wrote:

> 	  Have you also tried "lmer" in library(lme4)?  This is newer and 
> better in many ways.  Unfortunately, I see only one example in the Help 
> file, but you might be able to figure out how to use lmer from the help 
> file and from the 125 hits on RSiteSearch("lmer").
> 
> 	  The definitive work on this subject, from my perspective, is Pinheiro 
> and Bates (2000) Mixed-Effects Models in S and S-PLUS (Springer).  This 
> book is primarily how to use lme.  I learned a lot from it (and from 
> Doug Bates' other book with Don Watts on nonlinear regression).  I 
> couldn't find Pinheiro and Bates in the catalog for the library at 
> Universidad de Sevilla (though Bates and Watts was listed).
> 
> 	  Feel free to submit other questions after you've considered this, but 
> PLEASE do read the posting guide! 
> http://www.R-project.org/posting-guide.html first.  In particular, you 
> might have gotten a more helpful reply to this question if you had 
> included one of your attempts with "lme", asking what you did wrong or 
> what you don't understand about the results.
> 
> 	  Buena suerte,
> 	  spencer graves
> 
> Alfonso M Sanchez-Lafuente wrote:
> > Hi,
> > 
> > I am new to this list as a poster, but a reader for some time.
> > 
> > I've using R for several weeks now, and I have a lot of questions about 
> > certain procedures. Here I go:
> > 
> > I want to test if there are differences in the time spent by pollinators 
> > visiting flowers of a given plant species, according to a number of 
> > experimental manipulations made on those flowers. All experimental 
> > manipulations (factor with 5 levels) are replicated within plants (i.e. 
> > plant is my sampling unit). Further, I have two populations (two level 
> > factor), and a number of pollinator groups (again, two levels, the same 
> > in both populations). The response variables in the numbe of seconds 
> > invested in each probe. Further, I have plant floral display as a 
> > covariate, as it may influence visitation rates.
> > 
> > I think I have to analyse this desing considering population, pollinator 
> > group and their interaction as fixed effects, and treatment nested 
> > within plant, and its interaction with population and pollinator group, 
> > as random factors.
> > 
> > In SAS terminology, the model looks like this:
> > 
> > proc mixed data=flwfunc.visitflower covtest method=reml;
> >      class site pollclass treatm plantid;
> >      model time = site|pollclass flwinflor / chisq;
> >      random treatm site*treatm pollclass*treatm / subject=plantid;
> >      lsmeans site pollclass site*pollclass;
> > run;
> > 
> > I've been successfully trying lm, but I think is not suitable for random 
> > effects. Thus, I've tried lme, but no success when defining the random 
> > part or trying to interpret the results...
> > 
> > Any help will be welcome!
> >
> 
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