[R] help im lme()

[Dimitris Rizopoulos]

you can get the estimated covariance matrix of the random-effects 
using:

library(nlme)
m <- lme(Orthodont)

# scaled by the residuals variance
pdMatrix(m$modelStruct$reStruct)

# raw
lapply(pdMatrix(m$modelStruct$reStruct), "*", m$sigma^2)


However, it seems that in your model you use as a fixed-effect your 
grouping factor "ano", which is not in the spirit of mixed-models.


I hope it helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/336899
Fax: +32/16/337015
Web: http://www.med.kuleuven.ac.be/biostat/
     http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "Bernardo Rangel Tura" <tura at centroin.com.br>
To: <r-help at stat.math.ethz.ch>
Sent: Thursday, March 31, 2005 11:21 AM
Subject: [R] help im lme()


> Hi R people!
>
> I have a doubt in lme().
> I use this model:
>
> m2.lme<-lme(log(cmort)~idade+ano,random=~idade|ano,data=dados)
>
> If i use summary I recive this output:
>
> > summary(m2.lme)
> Linear mixed-effects model fit by REML
>  Data: dados
>        AIC      BIC    logLik
>   1139.313 1170.554 -562.6563
>
> Random effects:
>  Formula: ~idade | ano
>  Structure: General positive-definite, Log-Cholesky parametrization
>             StdDev       Corr
> (Intercept) 3.131076e-03 (Intr)
> idade       3.515018e-05 -0.042
> Residual    5.687940e-01
>
> ...etc...
>
> I know the value of Residula random effects is m2.lme$sigma but how 
> do I find the value of idade or intercept random effects
>
>
> Thanks in advance
>
> Bernardo Rangel Tura, MD, MSc
> National Institute of Cardiology Laranjeiras
> Rio de Janeiro Brazil
>
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