# Can I test the effect of Block in a split plot design in R?

I have been confused with the problem for a very long time, and hope that somebody here can help me out.

I have a experiment installed in split-plot design, with 3 temporal groups as blocks, and 2 factors (each have 3 fixed levels) combinations in each of the block, and I have 4 replicates in each treatments. I used to build the model like this:

model <- aov(Var ~ Block+A*B+Error(Block/A/B), data)


where A and B are fixed factors of my focus. It seems that R will calculate the Block as an error term, where only DF, SS and MS were reported, but not F-ratio and p-value. My question is: is it make sense for me to estimate the effect of block (i.e. different time period) in R?

Actually, the 4 replication were sampled in four continuous days to develop a temporal sequence for another analysis. I would like to know how could I test the sampling effect, is it another block, or could be treated as a fixed factor nested within the treatment?

I think you know this already, but you can calculate the F Statistic by the ratio of MS and the F Statistic follows $F_{df1, df2}$ where df1 and df2 are degrees of freedom of the numerator and denominator.