[R-sig-ME] Covariance structure used in lme

[Sorkin, John]

I am running the following random slope, random intercept model:
#  Model 3
fitRSlope1 <- lme(distance~age+Sex+age*Sex, random=~1+age|Subject,data=Orthodont)
summary(fitRSlope1)
ranef(fitRSlope1)

When I run the model, I get the following output

Random effects:
 Formula: ~1 + age | Subject
 Structure: General positive-definite, Log-Cholesky parametrization
            StdDev    Corr
(Intercept) 2.4055009 (Intr)
age         0.1803455 -0.668
Residual    1.3100396

Is the general positive-definite, Log-Cholesky parametrization a description of what one might call an unstructured variance-covariance matrix with as a particular paramaterization?

Thank  you,
John





John David Sorkin M.D., Ph.D.
Professor of Medicine
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology and Geriatric Medicine
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)


	[[alternative HTML version deleted]]