[R-sig-ME] Compound Symmetry Covariance structure
jo@quin@@ld@be @ending from gm@il@com
Sat Dec 8 10:30:04 CET 2018
Hi, random effects induce correlation through a covariance matrix (G
matrix) , in nlme using compound symmetry as default. If variance
component of random effect are close to zero you may be having fitting
problems or the random intercepts is not that important.
Hooe this helps
El vie., 7 de dic. de 2018 3:15 PM, Yashree Mehta <yashree19 using gmail.com>
> I have a question about the random effects model (Specifically, a random
> intercept model) in its role in assuming a covariance structure in
> estimation. In a panel data textbook, I read that by estimating a random
> effects model itself, there is an induced covariance structure.
> In nlme package, there are several types of covariance structures such as
> Compound Symmetry (which I assume in my model) but the default value is 0.
> I initialize it and proceed with the estimation.
> Does this mean that if I do not specify the compound symmetry value in
> nlme, the estimation is without a covariance assumption or there is
> something I have missed in my understanding? That the " by estimating a
> random effects model itself, there is an induced covariance structure"
> confuses me a little.
> It would be very helpful to get an explanation on this.
> Thank you very much!
> [[alternative HTML version deleted]]
> R-sig-mixed-models using r-project.org mailing list
[[alternative HTML version deleted]]
More information about the R-sig-mixed-models