Dear All
I have a repeated measures design in which abundance was measured
repeatedly over 10 months in three treatments (Tortoise A; Tortoise B and
control) established in 6 blocks, i.e. crossed fixed effects. My original
design incorporated two tortoises per treatment, however as fieldwork goes
I ended up losing some animals. Rather than lose a couple of enclosures in
the analysis and have to do a lmer, I thought I could include tortoise
weight as an explanatory variable. For my treatments, tortoise weight in
the control always = 0, while in general Tortoise A is twice as large as
Tortoise B except when I lost animals. Is this the correct model?
aov(Tel.ab~Tort.W+Treatment*Month+Error(Month/Block))
Or should tortoise weight be nested in Treatment, i.e not included as a
fixed factor but including the fact that tortoises species may have an
effect? I am utterly confused now as to whether that should be the case as
to some extent Tort.W and Treatment are correlated.
Any help would be much appreciated.
Many thanks
Christine
----------------------
Christine Griffiths
School of Biological Sciences
University of Bristol
Woodland Road
Bristol BS8 1UG
Tel: 0117 9287593
Fax 0117 925 7374
christine.griffi...@bristol.ac.uk
http://www.bio.bris.ac.uk/research/mammal/tortoises.html
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
