John:
Linear models can have different covariance structures to accommodate
certain dependencies in the data. The functions for data analysis in the
lme4 package are flexible and can be structured as such. For example,
when random intercepts only are included, this is akin to compound
symmetry, but when random slopes are also introduced in a repeated
measures mlm using lmer(), then you have a more general covariance
matrix.
This isn't really an R question and most of the texts on mlm deal with
this issue directly.
Harold
-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of John Christie
Sent: Monday, March 20, 2006 7:54 AM
To: R-help at stat.math.ethz.ch
Subject: [R] does lme repeated measures require sphericity?
I haven't been able to find an answer on this that's direct, only
implied. In several places I have read that when people asked for
sphericity tests they were guided toward lme or mlm models. But, there
is no direct indication that the lme method is not subject to the
sphericity assumption. In fact, it seems like it should be. Its just a
linear model that handles random and fixed effects. I imagine most
other parametric assumptions hold true.
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