lara,
you might consider using random effects to pick up unmeasured, latent
variation among groups or individuals. since you've explicitly measured
initial mass, this should be included as a fixed effect, as already
mentioned in the previous post. however, if there were substantial
variation among individuals based on attributes you didn't measure, you
might consider random intercepts or slopes for these. of course caution
should be used to avoid over fitting once you start including a bunch of
extra parameters with random effects, perhaps by using some model fit
metric that penalizes for the number of parameters (e.g. one of the
information criteria).
cory

-- 
Cory Merow
Department of Ecology and Evolutionary Biology
University of Connecticut
Homepage <http://hydrodictyon.eeb.uconn.edu/people/cmerow/home/Home.html>
<http://www.eeb.uconn.edu/people/cmerow/home/Cory_Merows_Home_Page.html>
'Give me 3 parameters and I will draw you an elephant. Give me 4 and I will
wag the trunk.'

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