I answer my own question.
I was disturbed by the syntax of the SAS code for "proc mixed", which uses
the same procedure for mixed or non mixed effect model. Moreover, the type
of variance-covariance structure is indicate by one parameter.
R is more intuitive and supple : there is two different fu
I would like to make clear that the SAS "unstructured" correlation matrix in
the second model was :
Estimated R Correlation Matrix for id 1
1 1. 0.8575 0.6984 0.4657 0.3165
2 0.8575 1. 0.8557 0.5670 0.4039
3 0.6984 0.8557 1.0
Hello R users,
I'm student and I'm actually having a lecture introducing repeated mesures
analysis. Unfortunately, all examples use SAS system...
I'm working with lme function (package "nlme"), and I'm using
extract.lme.cov (package "mgcv") to extract covariance structure of models.
One example
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