[R] Trouble phrasing an R command that will run the model i need (ANOVA, nested)
dalelemu at hotmail.com
Fri Mar 24 08:29:59 CET 2006
I have been trying to find the appropriate R command to analyse my datasets
according to a particular model. Unfortunately, my best attempts at doing so
have so far not worked.
I am wondering if anybody can help me to figure out what i've been doing
wrong, and what i need to do in order to use R correctly?
The model is an ANOVA with some crossed factors, interactions, and one
nested factor. I have listed them here:
(Factors "foresttype" through to "experiment" are all at the same level;
there is no nesting there, but the last factor listed is nested).
linelabel (nested within every cell)
...and these are the appropriate F-test error terms:
foresttype -> tested against foresttype:crosstype interaction,
everything else -> tested against linelabel(nested)
I expect unequal sample sizes, so i have been trying to do it using Type III
sums-of-squares. Now, that's the model that i'm trying to run in R. My
attempts so far have looked like this:
>prod.anova <- aov(yproductivity ~
After looking at the results of this model, my plan was to redo the model
with the foresttype:crosstype interaction as the Error() term, to get the
right F-test for "foresttype". Like so:
>prod2.anova <- aov(yproductivity ~
To produce an output, i have used the Anova() command, and specified Type
Unfortunately, i have run into a couple of problems with this approach. The
first is that using the "Anova()" command produces this error message:
Error in Anova(prod.anova, type = c("III")) :
no applicable method for "Anova"
I have looked through the manual (and various guides to using R for ANOVA),
but haven't found anything that refers to it, let alone explains it. It
looks (to me) like an extremely generic error message, which makes me think
i am simply not using the "Anova()" command in the right way. But if the
"Anova()" command is not appropriate, then i don't know how else to get the
output that i want (and what else would allow me to specify Type III SS).
That's my first problem; here's a second one: As soon as i enter that second
>prod2.anova <- aov(yproductivity ~
, i get this error message:
Error() model is singular in: aov(yproductivity ~ foresttype + region +
It looks to me as if R is saying that i have constructed the formula
incorrectly. I noticied that i had "foresttype:crosstype" listed twice in
the one formula, so i ran it again with "foresttype:crosstype" ommitted from
the formula itself, but still in the "Error()" term. That produces the same
error message as before.
I played around with it a bit, and found that i seemed to get this Error
message when an interaction term is present in the "Error()" part of the
formula. But i don't know why this should be, as i all the tutorials i have
read have led me to beleive that R has no problem with an interaction term
being used with the "Error()" command. And, aside from that, if i can't use
an interaction term in "Error()", then how else can i obtain my F-test for
I sought help for this, and it was suggested to me that i give up trying to
use "aov()" at all, and do it all using the "lme()" command in the lme4
I downloaded "lme4", and read over this page:
http://www.stat.ucl.ac.be/ISdidactique/Rhelp/library/lme4/html/lme.html , to
try and get an idea of how to construct my "lme()" command.
My first try was:
>lme(yproductivity ~ foresttype+crosstype, data=productivity, yproductivity
(I excluded interactions and "Error()", as i wanted to just get a feel for
what general formula worked before i made things more complex. My tactic was
to write out the formula i'd used earlier, separating it into a formula
containing only fixed factors, and a formula containing only random factors,
in accordance with the page referenced above.) Unfortunately, doing so
results in the error message:
Error: couldn't find function "lme"
So i couldn't even get far enough to see wether the formula i had
constructed was laid out in a valid way.
I am really lost at this stage. I suspect that i am using all the wrong
commands, in the wrong way. But i don't know how else to run this model; the
commands i've tried have been my best attempts.
If anyone can provide any guidance, i would really appreciate it.
- David Elliott
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