There is no generally agreed upon notion of random effects for quantile regression applications. Insofar as one is willing to accept the idea that random effects are just "shrunken fixed effects" one can consider similar schemes in the QR context; one such is described in
“Quantile Regression for Longitudinal Data,” J. of Multivariate Analysis, (2004), 91, 74-89. But there are many open questions, so this is not for the faint hearted and there is certainly no "official" code. url: www.econ.uiuc.edu/~roger Roger Koenker email [EMAIL PROTECTED] Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820 On Feb 5, 2008, at 9:40 PM, Beth Strain wrote: > > Dear R, > I have a question concerning quantile regression models. > > I am using the quantile regression model to test the relationship > between > abalone and the percentage cover of algae etc at different sites and > depths. > > An example is > fit<-rq(abalone~%coversessileinvertebrates+factor(Depth) > +factor(Site),tau=0.7) > > In this model depth is fixed and site is random. My question is, is it > possible specify the fixed and random effects in this model. If so > could > someone please give me an example of how to write the code. > > I can;t seem to find any information in the R help. > Thanks in advance > Beth Strain > > ______________________________________________ > 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.
