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...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]]

If I wanted to fit a logit model and account for clustering of observations, I would do something like: library(Design) f <- lrm(Y1 ~ X1 + X2, x=TRUE, y=TRUE, data=d) g <- robcov(f, d$st.year) What would I do if I wanted to do the same thing with a probit model? ?robcov says the input model must come from the Design package, but the Design package appears not to do probit? Thanks very