david_foreman@doctors.org.uk
2004-Jun-15 11:52 UTC
[R] fit.mult.impute and quantile regression
I have a largish dataset (1025) with around .15 of the data missing at random overall, but more like .25 in the dependent variable. I am interested in modelling the data using quantile regression, but do not know how to do this with multiply imputed data (which is what the dataset seems to need). The original plan was to use qr (or whatever) from the quantreg package as the 'fitter' argument in Design's fit.mult.impute, but it is not clear whether this would work, especially as fit.mult.impute seems only to work with the default settings of its 'fitter' arguments, which rather defeats the purpose of quantile regression. Help!! _______________________________________________________________________ Most doctors use http://www.Doctors.net.uk e-mail. Move to a free professional address with spam and virus protection.
Having not tried this, it is dangerous to speculate, but it appears to me that there would be no problem passing rq arguments (crucially, only tau, the specification of the quantile of interest) to fit.mult.impute, since the call to the "fitter" procedure includes a ... argument. The real question would seem to be: are the assumptions underlying the imputation procedure consistent with the rq fitting, that is are they assuming something stronger than that the tauth conditional quantile function of y is linear in x? There seem to be quite a variety of options for the imputation in transcan, maybe Frank could advise on this? url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820 On Jun 15, 2004, at 11:52 AM, <david_foreman at doctors.org.uk> wrote:> I have a largish dataset (1025) with around .15 of the data missing at > random overall, but more like .25 in the dependent variable. I am > interested in modelling the data using quantile regression, but do not > know how to do this with multiply imputed data (which is what the > dataset seems to need). The original plan was to use qr (or whatever) > from the quantreg package as the 'fitter' argument in Design's > fit.mult.impute, but it is not clear whether this would work, > especially as fit.mult.impute seems only to work with the default > settings of its 'fitter' arguments, which rather defeats the purpose > of quantile regression. Help!! > > > _______________________________________________________________________ > Most doctors use http://www.Doctors.net.uk e-mail. > Move to a free professional address with spam and virus protection. > > ______________________________________________ > R-help at stat.math.ethz.ch 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