I am having serious problems understanding the type of design I have, I would appreciate any help you can give me to understand it:
I have 324 data points, and four factors:
epochfactor, with three levels.
floorfactor, with three levels.
sitefactor, with nine levels.
timefactor, with three levels.
I have four points at each site, I have nine sites, these nine sites are divided in three, three sites correspond to the highest altitudinal floor, three to the middle altitudinal floor and three to the lower altitudinal floor, that give me a total of 36 points, in each point I took data three different times of day, giving me a total of 108 data points. And I repeated these procedure (the exactly same 36 points) in three epochs of the year.
In other words: Each epoch have 108 data points, these 108 are divided in three (the levels of altitudinal floor factor), 36 to each altitudinal floor, these 36 are divided in three (three levels of the site factor), 12 to each site, and these 12 are divided in three (the levels of time factor) each time have 4 data points.
I want know which anova is appropriate for test if there are differences at each factor: a nested anova:
aov(y ~ (epoch/floor/site/time), data=data)
or a split-plot anova:
aov(y ~ floor*site*time + Error(epoch/floor/site/time), data=data)
From what I've read, I think that is a nested design, but I dont understand why it is not a split-plot. Can anyone help me?