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Re: st: quasi-complete separation
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: quasi-complete separation
Date
Sun, 28 Aug 2011 17:29:02 +0100
I don't know where 48.5 comes from so I can't comment on that.
. input y x
y x
1. 0 1
2. 0 2
3. 0 3
4. 0 4
5. 1 1
6. 1 2
7. 1 3
8. 1 4
9. 1 5
10. 1 6
11. 1 7
12. end
. logit y x
Iteration 0: log likelihood = -7.2102995
Iteration 1: log likelihood = -6.3453449
Iteration 2: log likelihood = -6.31452
Iteration 3: log likelihood = -6.314268
Iteration 4: log likelihood = -6.314268
Logistic regression Number of obs = 11
LR chi2(1) = 1.79
Prob > chi2 = 0.1807
Log likelihood = -6.314268 Pseudo R2 = 0.1243
------------------------------------------------------------------------------
y | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
x | .5126268 .4305072 1.19 0.234 -.3311519 1.356405
_cons | -1.076253 1.436463 -0.75 0.454 -3.891669 1.739162
------------------------------------------------------------------------------
In my ignorance I was not aware until now of the terminology of
"quasi-complete separation" although Googling reveals several long
discussions. Evidently there are datasets which are difficult or
impossible to model with -logit- or -probit-. So, what else is new?
Whether it helps to use this terminology I don't know. It just sounds
like giving the problem a name to me. Others may be able to add deeper
comments.
Nick
On Sun, Aug 28, 2011 at 5:01 PM, Sabrina Helmut <[email protected]> wrote:
> Nick,
> thanks! You are right, logit works but the coefficient for the concerned variable is extremely high (48.5..) I will need an explanation for this. So, do you think my example shows quasi-complete separation which could be an explanation for the high coefficient?
>
> ----------------------------------------
>> Date: Sun, 28 Aug 2011 16:43:36 +0100
>> Subject: Re: st: quasi-complete separation
>> From: [email protected]
>> To: [email protected]
>>
>> Sabrina, and indeed anybody else: Please do not send, or attempt to
>> send, attachments to Statalist.
>> See http://www.stata.com/support/faqs/res/statalist.html#toask where
>> this is explained, twice over.
>>
>> Sabrina: -logit y x- will work with this dataset, but there is only a
>> weak relationship.
>>
>> Nick
>>
>> On Sun, Aug 28, 2011 at 4:24 PM, Sabrina Helmut <[email protected]> wrote:
>> > I am sorry, the scatter has not been send. Thus, an example for you:
>> >
>> > binary dependent variable y
>> > continuous variable x
>> >
>> > y x
>> > 0 1
>> > 0 2
>> > 0 3
>> > 0 4
>> > 1 1
>> > 1 2
>> > 1 3
>> > 1 4
>> > 1 5
>> > 1 6
>> > 1 7
>> >
>> > Thus, values of the independent variable being higher than 4 are only captured by y=1.
>> > So, is this a problem of quasi-complete separation? Thank you very much.
>> >
>> >
>> > ----------------------------------------
>> >> From: [email protected]
>> >>
>> >> I provided a scatter for you. Am I right with the assumption that it shows the problem of quasi-complete separation? Thanks.
>>
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