On Nov 30, 2010, at 13:58 , Hedberg Peter wrote:
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