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
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