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Re: st: mlogtest after mlogit


From   Chiara Mussida <cmussida@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: mlogtest after mlogit
Date   Tue, 25 Oct 2011 13:55:07 +0200

On 25 October 2011 13:30, Nick Cox <njcoxstata@gmail.com> wrote:
> Now we are really getting somewhere. "__000000" is a temporary name;
> in essence it surely does not belong there. I guess now that you have
> tickled a bug in one of the -spost- routines and, as recommended
> already in this thread, you should bring this to the attention of the
> authors, who as said are not active members of Statalist.
>
> Note that -_pecats- does find all your categories 1/9 which supports
> my earlier wild conjecture that their frequencies were not an issue.
>
> So, the warning message itself now appears to be an error, but there
> is no obvious reason to credit the rest of the output if -mlogtest- is
> misunderstanding what is going on with your model and data. You did
> not comment on the fact that -r(refval) is missing in your output, so
> other difficulties may lie undetected.
>
> Nick
>
Surely, I'm going to bring the attention of my problem to the authors
of mlogtest ado.
Nonetheless, the estimates of the mlogit for 9 categories do not seem
to be biased:
the results are consistent of previous findings obtained by running 3 separate
mlogit (3 mlogit with common origin state). My attempt to put all the
categories/outcome
 together is to avoid to get mixed up with sample selection issues.


> On Tue, Oct 25, 2011 at 12:18 PM, Chiara Mussida <cmussida@gmail.com> wrote:
>> On 25 October 2011 12:57, Nick Cox <njcoxstata@gmail.com> wrote:
>>> If you look at the code of -mlogtest- the warning message that worries
>>> you is when a helper program -_pecats- produces output that is
>>> inconsistent. After your -mlogit- call you can run -_pecats- followed
>>> by -return list-. In a well-behaved case, you will get output like
>>> this in which r(numcats) matches the number of elements in r(catvals).
>>> Your output will probably not match up. I don't know why that might
>>> be, but I doubt that the category frequencies are somehow the issue.
>>> (For "STATA" read "Stata".)
>>>
>>> . _pecats
>>>
>>> . return list
>>>
>>> scalars:
>>>            r(numcats) =  9
>>>             r(refval) =  3
>>>
>>> macros:
>>>            r(catnms8) : "1 2 4 5 6 7 8 9 3"
>>>            r(catvals) : "1 2 4 5 6 7 8 9 3"
>>>             r(catnms) : "1 2 4 5 6 7 8 9 3"
>>>              r(refnm) : "3"
>>>
>> Exactly Nick and thanks: when I type -_pecats- and -return list- I get:
>>
>>  return list
>>
>> scalars:
>>            r(numcats) =  9
>>             r(refval) =  .
>>
>> macros:
>>            r(catnms8) : "1 2 3 4 5 6 7 8 9"
>>            r(catvals) : "1 2 3 4 5 6 7 8 9 __000000"
>>             r(catnms) : "1 2 3 4 5 6 7 8 9"
>>
>> where as you correctly assumed, I do not have the match between
>> r(numcats) and  r(catvals), but something like __000000 which does not
>> allow a perfect matching. I still do not know why it happens.
>>
>>
>>
>>
>>
>>>
>>> On Tue, Oct 25, 2011 at 11:10 AM, Chiara Mussida <cmussida@gmail.com> wrote:
>>>> On 25 October 2011 01:10, Richard Williams
>>>> <richardwilliams.ndu@gmail.com> wrote:
>>>>> At 05:59 AM 10/24/2011, Muhammad Anees wrote:
>>>>>>
>>>>>> have you tried -mlogtest, all- to verify if these categories have no
>>>>>> other issues. Otherwise the test on -combine- might have resulted
>>>>>> becaure some of the categories had small or no observations so
>>>>>> checking the condition of equal coefficients from -comibe- did not
>>>>>> work.
>>>>>
>>>>> I agree - I get nervous about using multiple-outcome commands like mlogit
>>>>> with lots and lots of independent variables. You may be spreading the data
>>>>> too thin. But, before taking this too much further, I'd like the original
>>>>> poster to confirm that the most current version of mlogtest is indeed being
>>>>> used. Otherwise we might be talking about a problem that was fixed 6 months
>>>>> ago. Also, it might be good to present a frequency of the dependent
>>>>> variable. Long and Freese's commands are sometimes pickier about coding than
>>>>> Stata is, e.g. they sometimes don't like non-integer coding. Also, you would
>>>>> see if some of the categories have very small frequency counts. Finally, I
>>>>> would run a simple model with only one or two independent variables followed
>>>>> by mlogtest. If the simple model works and the more complicated one doesn't,
>>>>> that might indicate problems with one or more of the added variables or with
>>>>> the data being spread too thin to do the test.
>>>>>
>>>>>
>>>> Dear All, I confirm that my current version of mlogtest is and was the
>>>> one indicated by Nick, precisely:
>>>>
>>>> . which mlogtest, all
>>>>
>>>> C:\Program Files\Stata12\ado\updates\m\mlogtest.ado
>>>> *! version 1.7.6 jsl 2009-10-18
>>>>
>>>> in terms of model estimates, I guess that the issue is related to the
>>>> relative frequency of my dependent variables categories':
>>>>
>>>>  ta transition
>>>>
>>>>  transition |      Freq.     Percent        Cum.
>>>> ------------+-----------------------------------
>>>>          1 |        271        0.70        0.70
>>>>          2 |        132        0.34        1.04
>>>>          3 |      1,119        2.90        3.94
>>>>          4 |        379        0.98        4.93
>>>>          5 |        722        1.87        6.80
>>>>          6 |     13,959       36.17       42.97
>>>>          7 |        388        1.01       43.98
>>>>          8 |        168        0.44       44.41
>>>>          9 |     21,450       55.59      100.00
>>>> ------------+-----------------------------------
>>>>      Total |     38,588      100.00
>>>>
>>>> e.g., categories 2 and 8 might be too small. Now, I cannot collapse my
>>>> dep variable in a reduced number of categories and I hope that
>>>> notwithstanding the STATA alert message after typing the test command
>>>> (below I copied all the results) do not bias my results. ps: for the
>>>> test N=25441 since the model estimates are referred to a subsample
>>>> (aged 15-64) of the overall population (38588).
>>>>
>>>> mlogtest, c
>>>>
>>>> Problem determining number of categories.
>>>>
>>>> **** Wald tests for combining alternatives (N=25441)
>>>>
>>>>  Ho: All coefficients except intercepts associated with a given pair
>>>>     of alternatives are 0 (i.e., alternatives can be combined).
>>>>
>>>> Alternatives tested|     chi2   df   P>chi2
>>>> -------------------+------------------------
>>>>       1-       2  |   18.576    5    0.002
>>>>       1-       3  |    5.990    5    0.307
>>>>       1-       4  |   13.565    5    0.019
>>>>       1-       5  |  148.448 5 0.000
>>>>       1-       6  |  178.434    5    0.000
>>>>       1-       7  |   33.226    5    0.000
>>>>       1-       8  |   68.938    5    0.000
>>>>       1-       9  |  311.133    5    0.000
>>>>       2-       3  |   19.911    5    0.001
>>>>       2-       4  |   23.931    5    0.000
>>>>       2-       5  |   68.619    5    0.000
>>>>       2-       6  |   68.197    5    0.000
>>>>       2-       7  |   24.027    5    0.000
>>>>       2-       8  |   55.161    5    0.000
>>>>       2-       9  |  127.081    5    0.000
>>>>       3-       4  |   36.426    5    0.000
>>>>       3-       5  |  438.391    5    0.000
>>>>       3-       6  |  703.923    5    0.000
>>>>       3-       7  |   59.553    5    0.000
>>>>       3-       8  |  103.537    5    0.000
>>>>       3-       9  | 1130.422    5    0.000
>>>>       4-       5  |  197.002    5    0.000
>>>>       4-       6  |  103.387    5    0.000
>>>>       4-       7  |   91.631    5    0.000
>>>>       4-       8  |  132.381    5    0.000
>>>>       4-       9  |  530.943    5    0.000
>>>>       5-       6  |  592.783    5    0.000
>>>>       5-       7  |  192.566    5    0.000
>>>>       5-       8  |  142.185    5    0.000
>>>>       5-       9  |  281.162    5    0.000
>>>>       6-       7  |  520.969    5    0.000
>>>>       6-       8  |  430.911    5    0.000
>>>>       6-       9  | 5946.722    5    0.000
>>>>       7-       8  |   24.867    5    0.000
>>>>       7-       9  |  231.357    5    0.000
>>>>       8-       9  |   82.933    5    0.000
>>>> --------------------------------------------
>>>>
>
> *
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>



-- 
Chiara Mussida
PhD candidate
Doctoral school of Economic Policy
Catholic University, Piacenza (Italy)

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