Please read the first two paragraphs of Details from ?formula
Ok, I just did.
So, If I understand this properly, the term Plot*Day would include both the
main effects of a and b and their second order interactions. So it could be
written Plot + Day + Plot:Day.
The term Plot:Day includes only
David,
Please read the first two paragraphs of Details from ?formula
You can try out the formulas with the notation
> expand.formula <- function(f) colnames(attr(terms(f), "factors"))
> expand.formula(~a+b)
[1] "a" "b"
> expand.formula(~a:b)
[1] "a:b"
> expand.formula(~a*b)
[1] "a" "b" "a:b"
So what is the difference between a colon and an asterisk in this code? For
that matter what does the slash mean?
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On May 5, 2011, at 23:30 , Rovinpiper wrote:
> Thanks slre,
>
> I seem to be making some progress now.
>
> Using a colon instead of an asterisk in the code really changes things. I
> had been getting residual SS and MS of zero. Which is ridiculous. Now I get
> much more plausible values.
>
>
Thanks slre,
I seem to be making some progress now.
Using a colon instead of an asterisk in the code really changes things. I
had been getting residual SS and MS of zero. Which is ridiculous. Now I get
much more plausible values.
Also, When I used an asterisk instead of a colon It wouldn't give
>>> Rovinpiper 04/05/2011 22:43 >>>
>So this seems to indicate that I have what I want. I have two
>respiration data points at each plot on each day.
Yes; if you had only Plot+Day you'd have a completely balanced full
factorial ... for Plot and Day.
But I think I now see an answer to your puzz
And I responded as follows:
Hi,
Thanks for your advice. I tried using table() to check for missing
data. Here are the results:
> table(Combined.Plot)
Combined.Plot
60m A1 B1 B3 B4 C5 C9 D2 D9 F60m F8 Q7
34 34 3434 343434 3434 34 34 34
>
This response went to my email:
Without your data it's hard to say, but one possibility is that your
plots are nested within treatments instead of crossed, or that you have
something rather more cunning going on involving the Days. For example
if you had 8 days for six of your plots and another 8
Hi Richard,
Thanks for your advice.
I think that your suggestion is that I run the ANOVA with Combined.Plot as a
factor. I have tried that does not alleviate the problem.
Did I understand you properly?
Do you have another idea?
Thanks,
David
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Most likely your combined.trt is linearly dependent on the combined.plot
factor. Try
Anova.Trt.D.M.T.Pr.Model <- aov(Combined.Rs ~ as.factor(Combined.Plot)
.
and see if combined.plot now has the 11 df you are anticipating.
Rich
On Tue, May 3, 2011 at 3:37 PM, Rovinpiper wrote:
> I'm runn
I'm running an ANOVA on some data for respiration in a forest. I am having a
problem with my degrees of freedom. For one of my variables I get one fewer
degrees of freedom than I should.
I have 12 plots and I therefore expected 11 degrees of freedom, but instead
I got 10.
Any ideas?
I have some
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