Hello all, This may be a simple question to answer, but I'm a little bit stumped with respect to the calculation of the F statistics in nested anovas with unbalanced design in R.
In my case, I have 11 vegetation transects (with 1000 10cmx10cm squares), where we estimated shrub cover. We have two different treatments: wildfire (4 transects) and prescribed burning (7 transects) and we want to compare the mean shrub cover between the 2 different treatments. I guess that I have to apply a one-way nested anova (transect number within treatment) with unbalanced number of samples (4000 in wildfire vs 7000 in prescribed burning). Moreover, I have to correct the initial sample size (1000 squares) to a corrected sample size by spatial autocorrelation (which in fact, makes all the n different between transects). Can anyone, please, tell me how to do this in R? Do I need to use lme()? Or is it possible to do it using aov()? Thanks a lot! Francesc PhD student University of Barcelona ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
