Dear all, I have a probably silly question on how to specify model for a split-plot design and for a within-subject design (1way). I have two factors: factor A with 5 levels and factor B with 2 levels, for each level of factor A I have 4 subjects that experiment both levels of factor B, so this should be a split-plot design without blocking. I've read tons of vignettes, old emails and whatsoever, but I've found somehow diffrent informations concerning the most appropriate way to code this using aov and lme/lmer. My guesses are as follows: aov(y ~ A * B + Error(Subject), data = mydata) lme(y ~ A * B, random = ~1 | Subject, data = mydata) lmer(y ~ A * B + (1 | Subject), data = mydata) This should provide results for a split-plot design without blocks where F statistics are computed according to the correct error strata am I right? I'm a little bit confused because most examples on help pages and vignettes involve blocking which is not present here. Additionally, suppose that instead of analyzing all the data as a whole I split them according to levels of factor A, thus having 5 different within-subjects models to run, how am I supposed to code the Error terms appropriately? This is what I figured out, yet I'm not sure it's what I want: aov(y ~ B + Error(Subject/B), data = mydata2) lme(y ~ B, random = ~1 | Subject/B, data = mydata2) lmer(y ~ B + (1 | Subject/B), data = mydata2) Thanks Niccol?