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Re: st: mlogtest after mlogit
From
Chiara Mussida <[email protected]>
To
[email protected]
Subject
Re: st: mlogtest after mlogit
Date
Tue, 25 Oct 2011 13:18:20 +0200
On 25 October 2011 12:57, Nick Cox <[email protected]> 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 <[email protected]> wrote:
>> On 25 October 2011 01:10, Richard Williams
>> <[email protected]> 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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