There are two way to accomplish this in nlme. First try using the summary() command, which will produce all variance components and estimates for the fixed effects. Also, try the following to extract the point estimates and approximate CIs for the variance comonents.
> intervals(model.lme, which="var") Harold -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Steve Roberts Sent: Monday, April 05, 2004 3:32 PM To: [EMAIL PROTECTED] Cc: Steve Roberts Subject: [R] 2 lme questions Greetings, 1) Is there a nice way of extracting the variance estimates from an lme fit? They don't seem to be part of the lme object. 2) In a series of simulations, I am finding that with ML fitting one of my random effect variances is sometimes being estimated as essentially zero with massive CI instead of the finite value it should have, whilst using REML I get the expected value. I guess it is a numerical/optimisation problem but don't know enough about the lme fitting algorithm to know which tollerance/scale parameter to mess about with. Any suggestions where to start? Thanks, Steve. [[alternative HTML version deleted]] ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
