[R] Residuals of tobit{AER} and testing distribution normality
David Winsemius
dwinsemius at comcast.net
Wed Mar 26 22:06:14 CET 2014
On Mar 25, 2014, at 11:02 AM, Michal Kvasnička wrote:
> Hallo.
>
> What are the residuals returned by resid() in this code?
>
> library(AER)
> m <- tobit(y ~ x1 + x2, data=dat)
> rr <- resid(m2, type = "response")
>
> Can I use them to test the normality of the random variable distribution
> this way?
>
I understood tobit regression to not be assuming Normal distributions, but rather truncated Normal.
> qqnorm(rr)
> shapiro.test(rr)
That's not to say that the residuals are not supposed to be Normal. But most tests of normality are insensitive with small N and overly sensitive with large N, _and_ most methods are fairly robust to departures, so normality testing is either misguided or not necessary in most situations.
>
> And is it correct to handle heteroskedasticity of the model this way?
Correct? (... and I see not descriptions of any "handling" so did you mean "assessment" which I addressed above.) What are the real-world costs of an incorrect answer? are you doing anything for which estimates in the tail of your distributions would be critical?
>
> coeftest(m2, vcov=sandwich)
>
> Many thanks for any help or hint.
>
> Best wishes,
> Michal Kvasnicka
>
> [[alternative HTML version deleted]]
>
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David Winsemius
Alameda, CA, USA
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