R help - Feb 2011 - censReg or tobit: testing for assumptions in R?

Hello!

I'm thinking of applying a censored regression model to
cross-sectional data, using either the tobit (package survival) or the
censReg function (package censReg). The dependent variable is left and
right-censored.

My 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)?

(Or perhaps I'm on the wrong track in a more fundamental sense and
shouldn't be Iooking for equivalences to lm?)

Many thanks for any help.

EH

> I'm thinking of applying a censored regression model to
> cross-sectional data, using either the tobit (package survival) or the
> censReg function (package censReg). The dependent variable is left and
> right-censored.
  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.


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.

Terry Therneau