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Re: st: Normally distributed error term & testing normality of residuals


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Normally distributed error term & testing normality of residuals
Date   Sun, 14 Oct 2012 12:53:46 +0100

No one said that. You can plot the residuals, or their squares, or
their absolute values, or roots of absolute values -- there are
arguments for each -- against anything of interest, e.g. a predictor
or fitted values. See e.g.

SJ-4-4  gr0009  . . . . . . . . . . Speaking Stata: Graphing model diagnostics
        . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  N. J. Cox
        (help anovaplot, indexplot, modeldiag, ofrtplot, ovfplot,
        qfrplot, racplot, rdplot, regplot, rhetplot, rvfplot2,
        rvlrplot, rvpplot2 if installed)
        Q4/04   SJ 4(4):449--475
        plotting diagnostic information calculated from residuals
        and fitted values from regression models with continuous
        responses

for one broad discussion. That paper says nothing specific about
-tobit- models, however.

On Sun, Oct 14, 2012 at 9:54 AM, Ebru Ozturk <ebru_0512@hotmail.com> wrote:
> Thank you. So, there is no possibility to check heteroscedasticity graphically?
>
> Ebru
>
> ----------------------------------------
>> Date: Sat, 13 Oct 2012 18:25:14 -0400
>> Subject: Re: st: Normally distributed error term & testing normality of residuals
>> From: jvverkuilen@gmail.com
>> To: statalist@hsphsun2.harvard.edu
>>
>> On Sat, Oct 13, 2012 at 1:39 PM, Ebru Ozturk <ebru_0512@hotmail.com> wrote:
>> > With default do you mean without robust standard error or something else?
>> >
>> Yes, the default is OIM.
>>
>>
>> > ----------------------------------------
>> >> Date: Sat, 13 Oct 2012 11:57:59 -0400
>> >> Subject: Re: st: Normally distributed error term & testing normality of residuals
>> >> From: jvverkuilen@gmail.com
>> >> To: statalist@hsphsun2.harvard.edu
>> >>
>> >> On Sat, Oct 13, 2012 at 11:41 AM, Ebru Ozturk <ebru_0512@hotmail.com> wrote:
>> >> > Thank you very much. One last question altough it is slightly different from the main issue:
>> >> >
>> >> > In order to test heteroscedasticity assumption can I use scatter plots etc? or do I need to use a formal test like for testing normality issue?
>> >>
>> >> I think I'd probably use both, as the test just says "there appears to
>> >> be heteroscedasticity" but doesn't tell you much about what it might
>> >> be. One other quick and cheap diagnoser of heteroscedasticity is to
>> >> run with robust standard errors and with default. If they appear to
>> >> differ much, that's a sign you have a problem.
>> >> *
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