Hmmm, been away and got this... I appreciate the effort but there wasn't anything, in principle, in MASS on this I didn't already know. My question is just more about the functioning of the lm command and deriving these values. I understand that its the wrong approach for repeated measures design and lme is more appropriate. But, I wanted to examine / compare. So, my question still stands. How does one get something like the subject x effect interaction term from lm?
Also, while I'm at it, anyone familiar with Blouin & Riopelle on confidence intervals and repeated measures deigns? Is there a reason the intervals() command should give me different values for the narrow inference confidence intervals than they get from SAS? On May 17, 2007, at 2:20 PM, Bert Gunter wrote: > You need to gain some background. MIXED EFFECTS MODELS in S and S- > PLUS by > Pinheiro and Bates is a canonical reference for how to do this with R. > Chapter 10 of Venables and Ripley's MASS(4th ed.) contains a more > compact > but very informative overview that may suffice. Other useful > references can > also be found on CRAN. > > > Bert Gunter > Genentech Nonclinical Statistics > > -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of John Christie > Sent: Thursday, May 17, 2007 10:06 AM > To: [email protected] > Subject: [R] repeated measures regression > > > How does one go about doing a repeated measure regression? The > documentation I have on it (Lorch & Myers 1990) says to use linear / > (subj x linear) to get your F. However, if I put subject into glm or > lm I can't get back a straight error term because it assumes > (rightly) that subject is a nominal predictor of some sort. > > In looking at LME it seems like it just does the right thing here if > I enter the random effect the same as when looking for ANOVA like > results out of it. But, part of the reason I'm asking is that I > wanted to compare the two methods. I suppose I could get it out of > aov but isn't that built on lm? I guess what I'm asking is how to > calculate the error terms easily with lm. ______________________________________________ [email protected] 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.
