Re: st: How to get rid of outliers

[Sergiy Radyakin <serjradyakin@gmail.com>]

Xixi, listen to Nick's advice. But if you still want to drop them, here is how:

sysuse nlsw88
centile wage, c(2.5 97.5)
local l=r(c_1)
local r=r(c_2)
kdensity wage, xline(`l') xline(`r')
keep if inrange(wage, `l', `r')

Best, Sergiy Radyakin


On Thu, Oct 24, 2013 at 10:45 AM, Nick Cox <njcoxstata@gmail.com> wrote:
> If the question is simple
>
> How to get rid of outliers?
>
> then there is a good simple long answer
>
> Don't (usually).
>
> and a good simple short answer
>
> Don't.
>
> There are of course even longer answers in many places. The thread starting at
>
> http://www.stata.com/statalist/archive/2007-06/msg00185.html
>
> throws a variety of lights on outliers and immodesty leads me to recommend
>
> http://www.stata.com/statalist/archive/2007-06/msg00239.html
>
> as particularly long-winded, and respect leads me to nominate Richard
> Goldstein's concise remark
>
> http://www.stata.com/statalist/archive/2007-06/msg00240.html
>
> as most penetrating of all. But the whole thread is worth looking through
>
> One rather long footnote to the thread is provided by
>
> SJ-13-3 st0313  . . . . . . . . . . . . . .  Speaking Stata: Trimming to taste
>         (help trimmean, trimplot if installed)  . . . . . . . . . .  N. J. Cox
>         Q3/13   SJ 13(3):640--666
>         tutorial review of trimmed means, emphasizing the scope for
>         trimming to varying degrees in describing and exploring data
>
> but the best Stata incantation of all is likely to be -glm-.
>
> More generally, modify your model so that outliers are accommodated.
>
> Don't modify your data because they are awkward to analyse.
>
> Nick
> njcoxstata@gmail.com
>
>
> On 24 October 2013 15:31, Xixi Lin <winnielxx@gmail.com> wrote:
>> Hi All,
>>
>> I know it seems to be a very simple question. But I still wanna ask
>> how to keep 99%(95%) of the data? Is it just chop off 2 standard
>> deviations? How to code it then?
>>
>> Thanks a lot.
>>
>> Best,
>> Xixi Lin
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