[R] Why do I get (not estimable) in this aov data
Hedberg Peter
phedberg at biol.uw.edu.pl
Thu Dec 2 10:17:45 CET 2010
I realize the problem now, and you are right aov is wrong.
It seams that it was completely wrong to use the transect in a fixed formula, since my Trasects are labeled A to P, and A to D is in one mainplot, E-H in another, I-L an a third, and M-P in a fourth. In this case lme, with random variables for Transect is better. Thank you for the help.
Best regards, Petter
Peter Dalgaard <pdalgd at gmail.com> skrev :
> On Nov 30, 2010, at 13:58 , Hedberg Peter wrote:
>
> >> aov_data
> > Call:
> > aov(formula = Species1 ~ Site + Obstacle + Treatment + as.factor(Dist_Obstacle) +
> > as.factor(Dist_start) + Transect + Mainplot + Obsplot)
> >
> > Terms:
> > Site Obstacle Treatment as.factor(Dist_Obstacle) as.factor(Dist_start) Transect Obsplot Residuals
> > Sum of Squares 2143.984 446.274 340.042 736.073 173.707 800.270 4014.378 17238.625
> > Deg. of Freedom 2 1 1 4 3 10 60 271
> >
> > Residual standard error: 7.97566
> > 27 out of 109 effects not estimable
> > Estimated effects may be unbalanced
> >
> >
> >
> > My question is why do I get "effects not estimable", and "effects may be unbalanced). I have checked the data and it is balanced.
>
> Unfortunately, your attachment did not contain the data, but the sum of the Deg. of Freedom above is 352, suggesting that the observation count is 353, which is prime, so I find it difficult to believe that you have balanced data in the sense of a complete factorial design, even for a subset of your factors. A complete factorial with those DF would take more than 160000 observations!
>
> I suspect that aov() is simply the wrong tool for these data. lm() will do it, but watch out for the aliased effects.
>
> --
> Peter Dalgaard
> Center for Statistics, Copenhagen Business School
> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
> Phone: (+45)38153501
> Email: pd.mes at cbs.dk Priv: PDalgd at gmail.com
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