Hi list,

I have the feeling this came through the list and my message bounced, if it
did not excuses for double posting.

Using mixed models has been a while for me so I'm struggling with
recreating an approach as described in this publication (Banin et al. 2012:
http://onlinelibrary.wiley.com/doi/10.1111/j.1466-8238.2012.00778.x/full).

A description of the methodology is described here: "To determine whether
curve parameters were significantly different amongst all pairs of
continents, the dataset was split into all possible paired combinations and
a full model (where continent was specified as a fixed factor to provide
separate estimates for two continents) compared to a reduced model (where
data for the two continents were pooled) (Motulsky & Christopoulos, 2004)...

... Full and reduced models were compared using AICs and likelihood ratio
tests, which provide a p-value and an opportunity to assess whether models
provide a significant improvement (Pinheiro & Bates, 2000) . "

The model or curve as mentioned above is defined as

H ~ a - b * exp(-c * DBH) where H and DBH are the measured tree height and
tree diameter at breast height, respectively, see equation 1, in the above
paper.

DBHmodel <- function(x,a,b,c){a-b*exp(-c*x)}

Instead of continents I would like to pairwise compare site locations,
hence the setup will not change as I will substitute 'continent' for 'site'.

I define the 'full' model as such:

dataGrouped <- groupedData(height~dbh | site, data=data)
model1 <-
nlsList(height~DBHmod(dbh,a,b,c),data=dataGrouped,start=list(a=40,b=40,c=0.02))
model1.nlme <- nlme(model1)

This gives me two site based models but I'm at a loss on how to 1) define
the reduced 'population' model such such that it plays nicely with nlme and
treats the data as 'one' 2) perform the likelihood ratio tests on this due
to the lack of the former.

Any help is appreciated while I wander through Pinheiro and Bates to look
for a solution as well. I feel that this should be trivial but I'm still
lost in the nlme model formulation.

Kind regards,
K

-- 
Dr. Koen Hufkens

Harvard University
Department of Organismic & Evolutionary Biology
Richardson Lab
~
Ghent University
Faculty of Bioscience Engineering
Isotope Bioscience Laboratory
<http://www.isofys.ugent.be>

	[[alternative HTML version deleted]]

