Hi all, after browsing the archives for hours I'm still not sure about the proper analysis for my dataset.
I subjected each of about 50 critters (about 10 each in 5 distinct populations) to 4 consecutive treatments (exposure to increasing concentrations), with one measurement per treatment and individual. I, of course, want to know, if there was a treatment and / or a population effect. Since I'm dealing with 'paired' data, and also with a (expected) 'linear' response to a 'linear' treatment, how do I perform the proper analysis? I tried something like: summary(aov(y~group+treatment) summary(lme(y~group+treatment) but I don't see, how these formula would differentiate between a 'paired' or 'unpaired' experimental design. Somewhere in the archives it was mentioned that you could use the error-term to make that distinction (Baron-rpsych.pdf, pp.36-) summary(aov(y~group+treatment+Error(?), na.action=na.omit) summary(lme(y~group+treatment,random=~1|?,na.action=na.omit) but, unfortunately, that level of sophistication is still beyond my statistical powers. Any advice on the matter would be very much appreciated Wolfgang ______________________________________________ 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.