Thanks for your response!
Terry Therneau wrote:
I assume you mean "survreg" in the survival package. It's a shame
that censored gaussian regression has earned a unique label (tobit) that
makes people think it is something so very different.
(yes, what I meant was the function tobit() from the AER package, which
however interfaces the survreg function from the survival package:
http://rgm2.lab.nig.ac.jp/RGM2/func.php?rd_id=AER:tobit)
M>y hopefully not too silly question is this: I understand that
heteroskedasticity and nonnormal errors are even more serious problems
in a censored regression than in an ols-regression. But I'm not sure
how to test for these assumptions in R? Is there a way to get to the
residuals of censored regression models (given that corresponding
functions for lm, such as rstandard, are not applicable)?
Actually it can be less of a problem, since the really large outliers
often turn into censored observations, limiting their leverage.
For examination, there are good ideas in the article referenced
by ?residuals.survreg.
Many thanks for this hint, I will definitely check it out.
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