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Re: st: Normally distributed error term & testing normality of residuals
From
"JVerkuilen (Gmail)" <[email protected]>
To
[email protected]
Subject
Re: st: Normally distributed error term & testing normality of residuals
Date
Sat, 13 Oct 2012 09:42:38 -0400
On Sat, Oct 13, 2012 at 9:27 AM, Ebru Ozturk <[email protected]> wrote:
> Thanks. I checked it too. But I just wanted to learn is there a way of testing normality apart from a formal test like histogram, scatter plots?
Ah, yes, I get that point. Well the trick is that the observed data
are what they are but we don't know the censored data.
I can think of a few "devices" but I'm not sure what good properties
they would have. Cameron and Trivedi mention (but do not show) the
notion of comparing the predicted values for non-censored cases to the
observed values. The distribution won't be normal for them and the
relationship won't be perfectly linear, but you shouldn't see gross
differences in a good fitting model.
Example:
sysuse auto
gen wgt = weight/1000
tobit mpg wgt, ll(17)
predict predicted, xb
predict seforecast, stdf
gen censored = 0
replace censored = 1 if mpg <= 17
summarize mpg predicted if censored == 0, detail
cor mpg predicted
qqplot predicted mpg if censored == 0
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