[R] crossed random effects

[Sarah Mclean]

Hi,

thanks for the advice. I have looked at the Pinheiro
and Bates book and I've tried simplifying my model.

I've narrowed the problem down to having mum nested
within pop. If I run the analysis on each population
separately, the interaction between mo and su with mum
works fine.

If I could analyse all of the pops at once this would
be preferable because I have multiple responses and
pops to test so it would take a bit of time. I'm
hoping there is any easier way.

Thanks 
Sarah

 --- Spencer Graves <spencer.graves at PDF.COM> wrote: > 
  Have you studied Pinhiero and Bates (2000) Mixed
> Effects Models in S 
> and S-Plus (Springer)?
> 
> 	  Also, have you tried simplifying your "lme" call
> until you get 
> something that works, then start adding back terms
> in various 
> configurations until it breaks?
> 
> 	  Have you tried to compute how many coefficients
> are estimated in both 
> fixed and random terms and evaluate whether all are
> estimable?  For 
> example, with 2 factors at 2 levels each, if you
> don't have all 4 
> possible combinations, you can't estimate the
> interaction -- even if you 
> have thousands of replications of each.
> 
> 	  Finally, you can always try to read the code. 
> I've learned a lot 
> about S-Plus / R by doing that -- and solved a lot
> of my own problems 
> that way.
> 
> hope this helps.  spencer graves
> 
> Sarah Mclean wrote:
> > Hi,
> > 
> > if I have posted this twice, please ignore this.
> I'm
> > not sure if I sent it to the correct e-mail
> address
> > the first time.
> > 
> > I have a data set on germination and plant growth
> with
> > the following variables:
> > 
> > dataset=fm
> > mass (response)
> > sub (fixed effect)
> > moist (fixed effect)
> > pop (fixed effect)
> > mum (random effect nested within population)
> > iheight (covariate)
> > plot (random effect- whole plot factor for
> split-plot
> > design).
> > 
> > I want to see if moist or sub interacts with mum
> for
> > any of the pops, but I am getting an error
> message. 
> > 
> > This is the formula I used:
> > fm$pmu <- getGroups(fm, ~1|pop/mum, level=2)
> > fm$grp = as.factor(rep(1,nrow(fm)))
> > fm$pl <- getGroups(fm, ~1|plot)
> > fm$mo <- getGroups(fm, ~1|moist)
> > fm$su <- getGroups(fm, ~1|sub)
> > 
> >>fm1 <- lme(sqrt(mass) ~ iheight + moist*sub*pop,
> > 
> > data=fm,
> random=list(grp=pdBlocked(list(pdIdent(~pl -
> > 1), pdIdent(~pmu - 1),  pdIdent(~pmu:su - 1),
> > pdIdent(~pmu:mo - 1)))))
> > Error in chol((value + t(value))/2) : non-positive
> > definite matrix in chol
> > 
> > I know the problem is with the random interaction
> > terms, but I don't know how to overcome this.
> > 
> > Any advice would be greatly appreciated. I'm new
> to R
> > and analysis such as this.
> > 
> > Thank you,
> > 
> > Sarah Mclean
> > sarahmclean9 at yahoo.co.nz
> > 
> > 
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