[R-sig-ME] results lme unstructured covariance matrix, again

[ben pelzer]

Sorry, my previous mailed contained another question which is irrelevant...
I deleted that now.


Hi all,

I have a question about results from lme of package nlme.

Suppose the data consists of repeated measures at two fixed time points.

I used the following equation:



Model1 <- lme ( y ~ 1+t2 , random = ~ 0 + t1+t2|person, data=da)



y is the dependent, t1 and t2 are binary dummy variables, valued 0 or 1,
indicating the time point.  Model1 is estimated without any convergence
problems and the reproduced (co)variances found with



getVarCov(Model1, type=”marginal”, indivual=”1”)



are identical to the observed (co)variances.


My question is:  how can lme estimate 4 (co)variances with only 3 known
(co)variances?



The 4 estimates concern:

-          std. deviation of the random effect of dummy t1

-          std. deviation of the random effect of dummy t2

-          covariance of the random effects of the dummies t1 and t2 t1

-          residual std. error



Related to the question above: how can the variances of the random effects
and the residual std. error be interpreted?



Thanks for any help,



Ben.

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