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Re: st: Dopping 1% observations, but numbers do not match


From   Nick Cox <njcoxstata@gmail.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: Dopping 1% observations, but numbers do not match
Date   Wed, 10 Apr 2013 12:15:05 +0100

It's not a good idea to use code you don't understand!

I understand you as indicating that you are unclear about what [_N]
implies under -by:-. My numbered point #3 put it in words. I wrote a
tutorial which is easily accessible (there's a .pdf online, as below),
so I won't add to what I have written.

SJ-2-1  pr0004  . . . . . . . . . . Speaking Stata:  How to move step by: step
        . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  N. J. Cox
        Q1/02   SJ 2(1):86--102                                  (no commands)
        explains the use of the by varlist : construct to tackle
        a variety of problems with group structure, ranging from
        simple calculations for each of several groups to more
        advanced manipulations that use the built-in _n and _N

http://www.stata-journal.com/sjpdf.html?articlenum=pr0004

Technique for what you are asking is exemplified by

sysuse auto
su mpg, detail
scalar p1 = r(p1)
count if mpg <= p1
drop if mpg <= p1

but I can't write it down without flagging that I don't recommend
-drop-ping like this.

Nick
njcoxstata@gmail.com

On 10 April 2013 12:01, Miguel Angel Duran <maduran@uma.es> wrote:
> Thank you very much, Nick, for your quick answer. Just one additional
> questin, if you don't mind. How would I drop unconditionally on the
> identifier? And in relation to this (given your answer, just to be sure I
> got it right), when an expression like "var[_N]" is used, what does it
> exactly mean?

Nick Cox

> Numerous problems here, at least potentially.
>
> 0. Dropping outliers defined by an arbitrary threshold is not everyone's
> idea of good data analysis practice. If you want comments on what is
> "right", this needs defending.
>
> 1. Just because 0.0388193 is reported as the 1% point does not mean that
> exactly 1% of observations have that value or less, even in a situation
> where 1% of the number of observations is an integer. There could be ties.
>
> 2. Precision. 0.0388193 can't be held exactly as a binary number.
> Perhaps what is reported as that is really something else, e.g.
>
> . di %21x 0.0388193
> +1.3e01f8fe83ff0X-005
>
> . di %21x 0.03881931
> +1.3e01fe5ce7b79X-005
>
> . di %21x 0.03881929
> +1.3e01f3a020467X-005
>
> The number of decimal places you see does not correspond to what Stata holds
> in storage.
>
> 3. You are dropping if and only if _all_ values for each identifier are less
> than equal to your threshold. But that would leave in the data any such
> values if there were a greater value for the same identifier. That is, you
> are dropping conditionally on the identifier, not unconditionally.
>
> Nick
> njcoxstata@gmail.com
>
> On 10 April 2013 11:22, Miguel Angel Duran <maduran@uma.es> wrote:
>
>> Will you please help me to know that what I am doing is right? To
>> eliminate outliers, I am trying to drop 1% of the observations with the
> lowest values.
>> To do so I use 'bysort entity (rcon1410a): drop if  rcon1410a[_N] <=
>> 0.0388193'. Note that 'entity' is id, 'rcon1410a' is the relevant
>> variable, and 1% of the observations has a value that is lower than
>> 0.0388193 (this value is obtained from 'sum rcon1410a, detail'). Since
>> I have 415,000 observations, I should be dropping 1%*415,000=4,150.
>> Nevertheless, Stata informs me that using the abovementioned command I
>> have dropped 400 observations. Is this all right?
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