I think that Richard may be correct. In my experience it's always a
bad idea to use numerical labels for factors, especially when
importing data from Excel. But why not do a str() on your data to
see whether R thinks that time is a factor or not? And if not, why
not convert time to factor before passing it to aov()? I'm a bit
uneasy over your use of the phrase "there are two factors of time";
that's not how most stats people would use the terminology and it
may indicate a misunderstanding. You probably mean that there are
two levels of the factor 'time'. Anyway, do str(your_data) and
see what it says.
-Peter Ehlers
Clayton Coffman wrote:
There are two factors of time, but they are evenly replicated across all the
other factors/levels. The experiment is perfectly balanced except for one
lost sample, which is deleted automatically in the aov. I am very certain
the analysis is correct. I think its merely a discrepancy between how aov
and TukeyHSD group the levels of the factor variable. Probably aov handles
any vector specified as a character vector, whereas TukeyHSD merely assumes
its a character vector.
It might be something to refine in the stats package so the functions, which
are designed somewhat to be used together, can work on the same kinds of
data.
On Tue, Oct 20, 2009 at 6:13 PM, Richard M. Heiberger <r...@temple.edu>wrote:
Now I am worried that you have a wrong analysis.
the aov function is perfectly happy using either factors or
numeric variables. Are there really only two levels of time,
which is what one degree of freedom for time suggests? Or are there
more than two level, but since aov() sees that as a numeric variable
it has only one df.
csv files can interfere with the interpretation of data values, but
not likely in this case. They too will have numbers interpreted
as numeric.
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