Dear List,
I am realtively inexperienced so i apologise in advance and ask for
understanding in the simplicity of my question:
I have data on the amount of grass per km in a cell ( of which i have
lots) "grass" and for each cell i have x/y coordinates - required due
to spatial autocorrelation
Cells can be classfied in a hierarchical nature into AREAS and STATES
i.e Cell 1, Cell 2, Cell 3 are all in AREA "A"
where as Cell 4,5 and 6 are in AREA "B"
However both area A + B are in state "S1"
I have lots of these (13000) cells which are classfied into ~2000
AREA's and ~750 STATE'S
So my question is do AREA'S differ in the amount of grass they contain
i.e does AREA A contain significantly more grass than AREA B?
I have modelled this by
area_grass <- gls(grass~AREA, correlation=corExp(form=~x+y), data = grassland
I have set the contrasts to options(contrasts = c("contr.treatment",
"contr.poly")) as there are no control groups.
What i will get ( it is taking ages!)
is
AREA A: -0.12.... **
AREA B: 0.17....*
AREA C..
So can i then say AREA A has significantly less grass than the
average, AREA B significantly more and AREA C is not significantly
different?
Thanks
Alfreda
______________________________________________
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.
