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Re: st: How to get rid of outliers
From
Xixi Lin <[email protected]>
To
statalist <[email protected]>
Subject
Re: st: How to get rid of outliers
Date
Thu, 24 Oct 2013 13:32:39 -0400
William, Thank you so much for providing your notes.
Best,
Xixi Lin
On Thu, Oct 24, 2013 at 1:52 PM, Richard Williams
<[email protected]> wrote:
> Here are my notes on the causes and consequences of outliers and what to do
> about them. Discussion of solutions starts on p. 10. At a minimum you should
> check for coding errors. But there are a lot of other things I would do
> first before I simply got rid of them.
>
> http://www3.nd.edu/~rwilliam/stats2/l24.pdf
>
>
> At 11:31 AM 10/24/2013, Xixi Lin wrote:
>>
>> Thanks, that helps a lot!
>>
>> On Thu, Oct 24, 2013 at 11:55 AM, Sergiy Radyakin
>> <[email protected]> wrote:
>> > 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 <[email protected]> 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
>> >> [email protected]
>> >>
>> >>
>> >> On 24 October 2013 15:31, Xixi Lin <[email protected]> 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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>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
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>
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