Your question has some similarities this paper: Alison Smith, Brian Cullis, and Arthur Gilmour. The analysis of crop variety evaluation data in Australia. Aust. N. Z. J. Stat., 43:129--145, 2001.
In that paper, the authors fit a mixed model with several random effects. The variances are then held fixed while one of the model terms is changed from a random effect to a fixed effect and the model is re-fit using the constrained variances. They refer to this as "unshrinking" the BLUPs. This is accomplished with ASREML or the R version asreml-r, a commercial package (does have a 30-day free trial). Not sure if this would help you at all. Good luck, Kevin Wright On Tue, Jan 25, 2011 at 2:47 PM, Katharina Ley <kat...@umich.edu> wrote: > Hi, > > I am trying to manipulate a gls regression model output to adjust for use of > two-stage least squares. Basically, I want to estimate a model, then feed in > a new set of residuals, then re-calculate all of the model output (i.e. the > standard errors of the estimators, etc.). I have found some documentation on > doing this in stata, which is below: > http://www.stata.com/help.cgi?ereturn > > I am wondering whether there is a function like this ereturn() (see > http://www.stata.com/help.cgi?ereturn) in R, and whether this might allow me > to achieve something similar. > > Thanks so much! > > [[alternative HTML version deleted]] > > ______________________________________________ > 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. > -- Kevin Wright ______________________________________________ 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.
