[R-sig-ME] results lme unstructured covariance matrix, again
benpe|zer @end|ng |rom gm@||@com
Sat Jul 16 16:05:53 CEST 2022
Sorry, my previous mailed contained another question which is irrelevant...
I deleted that now.
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
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,
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