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Re: st: ladder question for right-skewed variable


From   Gabriel Nelson <[email protected]>
To   statalist <[email protected]>
Subject   Re: st: ladder question for right-skewed variable
Date   Fri, 26 Apr 2013 10:41:18 -0700

Thanks for the help David. Any idea why the ladder command would fail
to suggest transformations? I can see that the variable needs to be
transformed, and the variable does not show a bimodal structure. I am
worried that since the ladder command fails to run, there is some
other problem going on with the variable.

By the way, the variable measures the amount of people that report
being displaced by violence by municipality in Colombia.

Thank you,

Gabriel

On Thu, Apr 25, 2013 at 5:44 PM, David Hoaglin <[email protected]> wrote:
>
> Gabriel,
>
> The ratio of the largest value to the smallest value is quite large,
> so a transformation is likely to be useful.  As a first step ("first
> aid"), I suggest that you try the logarithm (base 10).
>
> Usually the context of the data plays a role in the choice of a
> transformation, so that the result is meaningful.  What is the nature
> of disp_2000?
>
> With 1010 observations you should check whether the data has some
> structure (e.g., two or more modes or groups), for example, by making
> a histogram with a sizable number of bins (say 25 or so).  If you find
> structure, you will need to deal with that also.
>
> David Hoaglin
>
> On Thu, Apr 25, 2013 at 8:11 PM, Gabriel Nelson
> <[email protected]> wrote:
> > I have a variable that is right-skewed.  I used the the ladder command
> > to see suggested transformations. However, no transformations appeared
> > in the output. I'm guessing that this does not mean the raw form is
> > better, because there is an option for 'raw' on this list.
> >
> > Here is the output for the sum, detail command for the variable:
> >
> >
> >
> > sum disp_2000, detail
> >
> >       Number displaced 2000 (if data unavailable go up
> >                            to 2003
> > -------------------------------------------------------------
> >
> >       Percentiles      Smallest
> >  1%            1              1
> >  5%            2              1
> > 10%            3              1       Obs                1010
> > 25%            6              1       Sum of Wgt.        1010
> >
> >
> > 50%         15.5                      Mean           281.5297
> >                         Largest       Std. Dev.      1217.168
> > 75%           82           9421
> > 90%        436.5           9505       Variance        1481497
> >
> > 95%         1251          16255       Skewness       9.012044
> > 99%         5953          19569       Kurtosis       108.8061
> >
> > Any suggestions are greatly appreciated.
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