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Re: st: collin
From
Aggie Chidlow <[email protected]>
To
[email protected]
Subject
Re: st: collin
Date
Sat, 12 Mar 2011 17:10:16 +0000
Here it is, I hope.
Variable | Obs Mean Std. Dev. Min Max
-------------+----------------------------------------------------------------------
y98 | 2252 .205595 .4042255 0 1
y99 | 2252 .2193606 .4139053 0 1
y00 | 2252 .1887211 .3913738 0 1
y01 | 2252 .1802842 .3845094 0 1
y02 | 2252 .1669627 .3730254 0 1
-------------+-----------------------------------------------------------------------
y03 | 2252 .0390764 .1938197 0 1
I think I can see the problem one, but I will wait for your response
to see if it matches yours.
On Sat, Mar 12, 2011 at 4:50 PM, DE SOUZA Eric
<[email protected]> wrote:
> If you had variables with the names y98 y99 y00 y01 y02 in your dataset, then -summarize y*- should produce one row under
> Variable | Obs Mean Std. Dev. Min Max
> for each of the variables:
> y98
> y99
> y00
> y01
> y02
>
> -----Original Message-----
> From: [email protected] [mailto:[email protected]] On Behalf Of Aggie Chidlow
> Sent: 12 March 2011 17:41
> To: [email protected]
> Subject: Re: st: collin
>
> Variable | Obs Mean Std. Dev. Min Max
> -------------+----------------------------------------------------------
> -------------+------------
> y_hat | 2251 .3609488 .1824771 4.26e-06 1
>
> This is the sum for y* (where y y98 y99 y00 y01 y02)
>
> Variable | Obs Mean Std. Dev. Min Max
> -------------+--------------------------------------------------------
> y_hat2| 2252 .3601243 .0537524 .102273 .3930885
>
>
> On Sat, Mar 12, 2011 at 4:16 PM, Nick Cox <[email protected]> wrote:
>> Your variables
>>
>> y y98 y99 y00 y01 y02
>>
>> should all be included in y*. Please show those too.
>>
>> Nick
>>
>> On Sat, Mar 12, 2011 at 4:10 PM, Aggie Chidlow
>> <[email protected]> wrote:
>>
>>> Here are the results for sum y*
>>>
>>> Variable | Obs Mean Std. Dev. Min Max
>>> -------------+-------------------------------------------------------
>>> -------------+------------
>>> y_hat | 2251 .3609488 .1824771 4.26e-06 1
>>
>> On Sat, Mar 12, 2011 at 3:52 PM, DE SOUZA Eric
>> <[email protected]> wrote:
>>
>>>> This is exactly what I thought you had, not just collinearity but perfect collinearity.
>>>> The question is: why are you getting perfectly collinearity?
>>>> Your y's appear to be constants.
>>>> Could you produce the results of -summarize y*- ?
>>
>> Aggie Chidlow
>>
>>>> Thank you for your advice... will definetly look this reference up.
>>>>
>>>> When I run my model with all dummies as the reviewer wants me to:
>>>>
>>>> probit y x1 x2 x3 lnx4 x5 y98 y99 y00 y01 y02
>>>>
>>>> where:
>>>> y98=463
>>>> y99=494
>>>> y00=425
>>>> y01=406
>>>> y02=376
>>>> y03=88 -not included in the model due to dummies trap
>>>>
>>>> I get the regression results that say the follwing:
>>>> note: y00 omitted because of collinearity
>>>> note: y01 omitted because of collinearity
>>>> note: y02 omitted because of collinearity
>>>>
>>>> The coefficients for y00 y01 and y02 are not reported in the model and there is a note which says y00 (omitted); y01 (omitted) and y02 (omitted).
>>>>
>>>> By the way the collin for year dummies is as follow:
>>>> Collinearity Diagnostics
>>>>
>>>> SQRT R-
>>>> Variable VIF VIF Tolerance Squared
>>>> ----------------------------------------------------
>>>> y98 -3.37e+13 . -0.0000 1.0000
>>>> y99 -3.53e+13 . -0.0000 1.0000
>>>> y00 -3.16e+13 . -0.0000 1.0000
>>>> y01 -3.05e+13 . -0.0000 1.0000
>>>> y02 -2.87e+13 . -0.0000 1.0000
>>>> y03 -7.74e+12 . -0.0000 1.0000
>>>> ----------------------------------------------------
>>>> Mean VIF -2.79e+13
>>>>
>>>> Cond
>>>> Eigenval Index
>>>> ---------------------------------
>>>> 1 2.0000 1.0000
>>>> 2 1.0000 1.4142
>>>> 3 1.0000 1.4142
>>>> 4 1.0000 1.4142
>>>> 5 1.0000 1.4142
>>>> 6 1.0000 1.4142
>>>> 7 0.0000 .
>>>> ---------------------------------
>>>> Condition Number .
>>>> Eigenvalues & Cond Index computed from scaled raw sscp (w/
>>>> intercept) Det(correlation matrix) -0.0000
>>>>
>>>>
>>>> On Sat, Mar 12, 2011 at 11:16 AM, DE SOUZA Eric <[email protected]> wrote:
>>>>> I haven't been following this thread till now.
>>>>> Jeffrey Wooldridge in his introductory textbook (page 99, international edition) does not encourage use of the VIF . The variance of a coefficient depends on three factors: the standard error of the regression, the total sample variation in the variable attached to the coefficient and the partial R2 . Concentrating on the partial R2 has no justification, even less so the rule of 10.
>>>>>
>>>>> However, in this case, the referee will probably have to be satisfied in some way or the other.
>>>>>
>>>>> Aggie, when you say that the dummies were dropped on account of collinearity, what exactly do you mean?
>>>>>> From: Aggie Chidlow <[email protected]> I was
>>>>>> appreciate some help regarding "collin"
>>>>>>
>>>>>> I just got a paper back from a reviewer and he/she wants me to
>>>>>> include all my year dummies (i.e. y98 y99 y00 y01 y02 y03) in the
>>>>>> following
>>>>>> model: probit y x1 x2 x3 lnx4 x5 y98 y99 y00 y01 y02
>>>>>>
>>>>>> Previusly in the model I only included two year dummies (i.e y99
>>>>>> and
>>>>>> y01) as the others we omitted automatically due to collinearity.
>>>>>> I mentioned that in the paper, however, he/she says it is
>>>>>> unsatisfactory and I should include them all and than comment on VIF.
>>>>>>
>>>>>> Please, can somebody tell me how I can go about this?
>>
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