Dear R users, I installed an experiment as following setup: - Four plant species - Seed addition as main factor with two levels: control and seed addition. - Four replicates (sites) - 8 plots in each site arranged as two rows (each rows 4 plots) one meter far from each other - Four sub-plots in each plot (therefore 32 sub-plots in each site) - In the four plots in each site (first row of plots) seeds of each of four plant species were sowed onto one sub-plot by random (therefore 4 sub-plots sown by a plant species in four different plots in each site). In the other four plots (second row of plots) one sub-plot selected by random as control for each of four plant species (therefore 4 sub-plots in four different plots in each site as control for a plant species). Now, my first question is about the name of this design. I thought this is a 3-factor split-plot arrangement. My second question is about data analysis for this experiment in R. I would like to test the effect of seed addition and sites on the seedling emergence of each plant species separately using a three- way ANOVA (??). Because of the hierarchical experimental design, the experiment must be analyzed by nested ANOVA but I do not know how I must arrange dataset and then how to write ANOVA model in R. I would greatly appreciate if somebody gives me some comments on these cases Thank you very much in advance, Majid -------------------------------------------------------------------------------- Majid Iravani PhD Student Swiss Federal Research Institute WSL Research Group of Vegetation Ecology Z?rcherstrasse 111 CH-8903 Birmensdorf Switzerland Phone: +41-1-739-2693 Fax: +41-1-739-2215 Email: Majid.iravani at wsl.ch http://www.wsl.ch/staff/majid.iravani/