Hi,
I'm working on leaf characteristics of trees. Each tree is characterised by about 10 leaf traits. The trees were sampled at 9 different locations (about 20 to 30 trees/location, NOT balanced), grouped in 3 different climatic zones (Sahelian, Soudanian and Guinean) (NOT balanced). Further, each tree is characterised by some degree of human pressure (mutilation degree), in total 4 different degrees were defined (NOT balanced). In the dryer zones, the trees are under a much higher human pressure than in the more humid climatic zones, "zone" and "mutilation degree" are thus strongly correlated. I want to know how "zones" (fixed effects, climate interests me) and "locations" (nested in "zones", random effects, location doesn't interests me) are influencing the leaf traits (say for example "SLA"). Further, also human pressure is affecting leaf traits so I want to characterise the influence of "mutilation degree" (fixed effects) on "SLA". I found some interesting information, but still, I am not be able to analyse the data properly. I think I have to use the function lme() or lme(). Can anyone tell me which function and command I have to use? And how I can produce an ANOVA table? Thanks in advance, Sebpe De Smedt [[alternative HTML version deleted]] ______________________________________________ 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.