The VarCorr function will extract the components of the random effects covariance matrix, but note the quirk that it returns values as characters:
library(nlme) f1 <- lme(distance ~ age, data = Orthodont, random = ~1 + age|Subject) (vc <- VarCorr(f1)) # Subject = pdLogChol(1 + age) # Variance StdDev Corr # (Intercept) 5.41508724 2.3270340 (Intr) # age 0.05126955 0.2264278 -0.609 # Residual 1.71620401 1.3100397 str(vc) # 'VarCorr.lme' chr [1:3, 1:3] "5.41508724" "0.05126955" "1.71620401" ... # - attr(*, "dimnames")=List of 2 # ..$ : chr [1:3] "(Intercept)" "age" "Residual" # ..$ : chr [1:3] "Variance" "StdDev" "Corr" # - attr(*, "title")= chr "Subject = pdLogChol(1 + age)" (sigma2.age <- as.numeric(vc[2, 1])) # [1] 0.05126955 hth, Kingsford Jones On Mon, Nov 16, 2009 at 9:25 AM, Green, Gerwyn (greeng6) <g.gre...@lancaster.ac.uk> wrote: > Dear all > > Apologies in advance as this seems like a trivial question. Nonetheless, > a question I haven't been able to resolve myself !. Within a single > repetition of a simulation (to be repeated many times) I am fitting the > following linear mixed model using lme... > > Y_{gtr} = \mu + U_{g} + W_{gt} + Z_{gtr} > > U_{g} ~ N(0,\gamma^{2}), W_{gt} ~ N(0,\kappa^{2}), Z_{gtr} ~ > N(0,\tau^{2}) > > g = 1,...,G > t = 1,...,T > r= 1,...,R > > > ...by doing > >> Model.fit <- lme(Y ~ 1, data=data, random= ~1|gene/treatment) > > I would like to be able to extract the estimated covariance parameters > contained within the lme object. I know if I type... > >> Model.fit$sigma > > > ...then I get the estimated residual variance, i.e. within the context > of the above model, the estimate for \tau. But I would also like to > extract the estimates for \gamma and \kappa by doing > Model.fit$"something". I am aware that I can view the output using the > extractor function "summary", but within a single repetition of my > simulation routine I want to be able to code something like > > gamma <- Model.fit$..... > kappa <- Model.fit$..... > > > and then plug `gamma' and `kappa' into some formulae. This process of > fitting and extracting will be repeated many times, which is why I wish > to automate everything. > > Again, any help would be greatly appreciated > > Best > > Gerwyn Green > School of Health and Medicine > Lancaster University > > > > > > > Any help would be greatly appreciated > > Best > > > Gerwyn Green > School of Health and Medicine > Lancaster Uinversity > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.