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Re: st: Normally distributed error term & testing normality of residuals
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: Normally distributed error term & testing normality of residuals
Date
Sat, 13 Oct 2012 14:05:09 +0100
The assumption of normality is here associated with a latent variable.
If the observed response is bounded, as is the whole point of tobit
model, what do you think that implies for the residuals?
By the way, if you are referring to the same problem as that discussed
in the lengthy thread starting in
http://www.stata.com/statalist/archive/2012-10/msg00187.html
then my position remains that tobit regression (or more precisely
interval regression) is quite inappropriate for that model.
Nick
On Sat, Oct 13, 2012 at 1:06 PM, Ebru Ozturk <[email protected]> wrote:
> Thank you Nick.
>
> I asked it for Tobit model.
>
> Ebru
>
> ----------------------------------------
>> Date: Sat, 13 Oct 2012 12:42:58 +0100
>> Subject: Re: st: Normally distributed error term & testing normality of residuals
>> From: [email protected]
>> To: [email protected]
>>
>> You don't say what kind of model you are fitting.
>>
>> -qnorm- allows a more incisive graphical assessment of normality than
>> -histogram, normal-. It doesn't offer a formal significance test.
>> People who are well informed on the matter don't agree: some would
>> always seek a formal test, others are happy to think about the results
>> of -qnorm- in context.
>>
>> Even when normality of error terms is an explicit assumption behind a
>> model, it is typically also the least important assumption.
>>
>> Nick
>>
>> On Sat, Oct 13, 2012 at 12:06 PM, Ebru Ozturk <[email protected]> wrote:
>>
>> > I test for normality of residuals with the command below:
>> >
>> > predict e, resid
>> > histogram e, normal
>> >
>> > So, does this command also work for understanding of whether error term normally distributed or not?
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