help im lme()
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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