First of all, I apologize for asking a question that has appeared recurrently in this mailing list. However, I have googled for it, have looked at the mailing list archives, and also looked at Pinheiro & Bates book (although not very thoroughly, I must confess), to no avail.
Here is the question: I am trying to obtain with lme or lmer the same exact numerical results (p-values) that I obtain with aov. Consider the following data: d <- data.frame (a = factor (rep (c (1, 2), c(10, 10))), b = factor (rep (rep (c (1, 2), c(5, 5)),2)), s = factor (rep (1 : 5, 4)), v = rnorm (20)) Let us say that this comes from a repeated measures experiments where all five subjects (factor s) were tested in all combinations of the two fixed factors a and b. With aov, for a model were s, s:a, s:b and s:a:b are random, and a*b are fixed terms, I would use: aov (v ~ a*b + Error (s / (a*b)), data = d) Is there a way to get the same results using lme or lmer? How should I write my "random" argument in lme or the "(...|...)" terms in lmer? Please notice that I am not interested in philosophical discussions about whether I am trying to do wrong things. I would only like to know whether a given R function could be used in place of another R function. Thanks in advance for your help, -- Rafael Laboissiere ______________________________________________ R-help@stat.math.ethz.ch 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.