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Re: st: xtlogit: panel data transformation's recast to double makes model incomputable


From   Nick Cox <njcoxstata@gmail.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: xtlogit: panel data transformation's recast to double makes model incomputable
Date   Wed, 3 Apr 2013 18:13:16 +0100

Update on -ladder-, following some experiments:

-ladder- breaks down for extreme sample sizes and/or extreme sample
skewness and kurtosis. Tom has both. Essentially either case yields
very low P-values, sometimes beyond the approximations that Stata
uses. The most fragile part is the default adjustment, which in fact
is carried out by -sktest-.

As reasonable transformations are not difficult to guess otherwise,
this isn't really a roadblock.

On 3 April 2013 17:10, Nick Cox <njcoxstata@gmail.com> wrote:
> So, it is not a problem with zero or negative values. I don't have an
> explanation for your difficulties with -ladder- otherwise.
>
> I don't think anyone needs a test to choose a transformation with 2
> million values that are manifestly highly skew.
>
> Your -summarize- results give min, max and nine quantiles in between.
> Transformations of interest are here all monotonic, so preserve order,
> so it is sufficient just to fire up Mata to look at what quantiles
> become, e.g.
>
> : y
>              1
>      +----------+
>    1 |     .02  |
>    2 |     .62  |
>    3 |    1.66  |
>    4 |    3.09  |
>    5 |    8.66  |
>    6 |   18.68  |
>    7 |   33.48  |
>    8 |   57.38  |
>    9 |   74.08  |
>   10 |  123.49  |
>   11 |  785.37  |
>      +----------+
>
> : log10(y)
>                    1
>      +----------------+
>    1 |  -1.698970004  |
>    2 |  -.2076083105  |
>    3 |    .220108088  |
>    4 |   .4899584794  |
>    5 |    .937517892  |
>    6 |   1.271376872  |
>    7 |   1.524785449  |
>    8 |   1.758760544  |
>    9 |   1.869700974  |
>   10 |   2.091631791  |
>   11 |   2.895074308  |
>      +----------------+
>
> : sqrt(y)
>                   1
>      +---------------+
>    1 |  .1414213562  |
>    2 |  .7874007874  |
>    3 |  1.288409873  |
>    4 |  1.757839583  |
>    5 |  2.942787794  |
>    6 |  4.322036557  |
>    7 |  5.786190457  |
>    8 |  7.574958746  |
>    9 |  8.606973917  |
>   10 |  11.11260546  |
>   11 |  28.02445361  |
>      +---------------+
>
> A glance shows that roots are not strong enough, but logarithms do
> much better, which matches a lot in economic thinking. However, it's
> one thing to make a distribution more symmetric; the question of how
> it behaves in a model remains.
>
> Nick
>
> On 3 April 2013 16:09, Tom <tommedema@gmail.com> wrote:
>> "close" is a price, and therefore it is always positive. -sum close,
>> detail- follows (after dropping some outliers in which I am not
>> interested):
>> http://pastebin.com/25gm94i0
>>
>> Because close is always positive I would like to return to the -ladder
>> close- issue. It turns out that when I supply -noadjust-, i.e. execute
>> -ladder close, noadjust- it does return some details:
>> http://pastebin.com/m8Z4YmKd
>>
>> -noadjust- is simply the -noadjust-  option of -sktest-, used by
>> -ladder-. The help file says that this is what it does:
>>
>>     " noadjust suppresses the empirical adjustment made by Royston
>> (1991) to the overall chi-squared and its significance level and
>> presents the unaltered test as described by D'Agostino, Balanger, and
>> D'Agostino (1990)."
>>
>> But does anyone have a clue why this adjustment would prevent ladder
>> from returning anything? Also see the results of -sktest close- versus
>> -sktest close, noadjust-:
>> http://pastebin.com/tPUf3xE6
>>
>> Tom
>>
>> On Wed, Apr 3, 2013 at 4:54 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>>> The transformations that -ladder- tries are typically only defined for
>>> positive variables. As I recall, many of your variables are variously
>>> positive and negative.
>>>
>>> The usual transformations for right-skewed variables, such as square
>>> root and logarithmic, are thus no use in your case.
>>>
>>> This is precisely why cube root and inverse hyperbolic functions were
>>> suggested earlier/
>>>
>>> On the face of it that is not an explanation of why all the
>>> transformations fail, but I'd not be inclined to think that -ladder-
>>> will help your problem.
>>>
>>> I'm afraid that you have keep reminding us of basics -- e.g. what is
>>> -close- and what are its descriptive statistics -- as even those
>>> following your threads can't be expected to keep track of all earlier
>>> posts.
>>>
>>> Nick
>>>
>>> On 3 April 2013 15:33, Tom <tommedema@gmail.com> wrote:
>>>
>>>> Anyway, I think I may have a very important pointer that could help in
>>>> finding the cause of this issue:
>>>> when I run -ladder close- it returns absolutely nothing, i.e.:
>>>>
>>>>  ladder close
>>>>
>>>> Transformation         formula               chi2(2)       P(chi2)
>>>> ------------------------------------------------------------------
>>>> cubic                  close^3                    .            .
>>>> square                 close^2                    .            .
>>>> identity               close                      .            .
>>>> square root            sqrt(close)                .            .
>>>> log                    log(close)                 .            .
>>>> 1/(square root)        1/sqrt(close)              .            .
>>>> inverse                1/close                    .            .
>>>> 1/square               1/(close^2)                .            .
>>>> 1/cubic                1/(close^3)                .            .
>>>>
>>>> I believe this is very much related to the problems I am having with
>>>> this variable, close. If I can determine why ladder refuses to give me
>>>> any transformations, then I may be able to figure out what is the
>>>> source of this issue.
>>>>
>>>> I am not just trying to get an answer, I am interested in why ladder
>>>> is not returning any transformations because this may give me
>>>> information on the root cause of the problem.
>>> *
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>> *
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>
>
>
> --
> Nick
> njcoxstata@gmail.com



-- 
Nick
njcoxstata@gmail.com
*
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