[R] fit.mult.impute and quantile regression

[david_foreman@doctors.org.uk]

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!!  


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