Thanks Marteen,
really useful i will take a look at the discussion, i will use that for
consistency with previous literature on the topic.
Cheers
cinzia
Maarten buis wrote:
>--- Cinzia Rienzo <[email protected]> wrote:
>> how do i remove the top and bottom 1% tails of the wage distribution
>> to remove outliers?
>
>Dropping parts of your data just because they have uncommon values is
>an extremeley bad idea. There has been a long thread on such ``mindless
>data dullifiers'' this week starting with this post:
>http://www.stata.com/statalist/archive/2007-06/msg00185.html
>
>If you still want to do this I would at least not drop those cases but
>create a variable (called touse) indicating which observations are to
>be used in the analysis (value 1) and which are to be ignored (value
>0). Than in your analysis commands you add -if touse-, like in the
>example below.
>
>*--------- begin example -------------
>sysuse nlsw88, clear
>sum wage, detail
>gen touse = inrange(wage, `r(p1)', `r(p99)')
>sum wage if touse
>*---------- end example --------------
>
>Hope this helps,
>Maarten
>
>-----------------------------------------
>Maarten L. Buis
>Department of Social Research Methodology
>Vrije Universiteit Amsterdam
>Boelelaan 1081
>1081 HV Amsterdam
>The Netherlands
>
>visiting address:
>Buitenveldertselaan 3 (Metropolitan), room Z434
>
>+31 20 5986715
>
>http://home.fsw.vu.nl/m.buis/
>-----------------------------------------
>
>
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