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Re: st: problem with Margin command and interaction graph in fixed effect logistic regression
From
Nahla Betelmal <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: st: problem with Margin command and interaction graph in fixed effect logistic regression
Date
Thu, 31 Oct 2013 16:51:46 +0000
Hi, thanks for your reply Alfonso. It is the nature of logistic fixed
effect not to report the constant. It does not report a constant
because it uses conditional ML to estimate the model, and the method
“conditions” the constant out of the likelihood function. Implicitly
there is a constant, but it’s just not estimated or reported.
the command I used is clogit Y i.DV i.DV#c.IVA i.DV#c.IVB i.DV#c.IVC,
group (i.fyear) or
which will be the same as if I used xtlogit, fe or
So we can not do anything to get the constant reported in the
regression, I was wondering if there is a way to get around that.
Maybe just plot the slops by specifying an expression of estimated
parameters that excludes or unifies the constant. I do not know really
how to do it , and I do hope that one of the members give insight into
this issue.
Many thanks again
Nahla
On 31 October 2013 16:15, Alfonso Sánchez-Peñalver
<[email protected]> wrote:
> Hi Nahla,
>
> I believe you are right in thinking that margins is not reporting the margins because you are estimating the model without a constant. I tried the following simple example:
>
> ------------------ begin code -----------------------
> sysuse cancer.dta, clear
> logit died i.drug##c.age studytime, noconst
> margins drug, at(studytime=(10(5)30))
> ------------------- end code -----------------------
>
> I get the following results:
>
> Predictive margins Number of obs = 48
> Model VCE : OIM
>
> Expression : Pr(died), predict()
>
> 1._at : studytime = 10
>
> 2._at : studytime = 15
>
> 3._at : studytime = 20
>
> 4._at : studytime = 25
>
> 5._at : studytime = 30
>
>
> Delta-method
> Margin Std. Err. z P>z [95% Conf. Interval]
>
> _at#drug
> 1 1 . (not estimable)
> 1 2 . (not estimable)
> 1 3 . (not estimable)
> 2 1 . (not estimable)
> 2 2 . (not estimable)
> 2 3 . (not estimable)
> 3 1 . (not estimable)
> 3 2 . (not estimable)
> 3 3 . (not estimable)
> 4 1 . (not estimable)
> 4 2 . (not estimable)
> 4 3 . (not estimable)
> 5 1 . (not estimable)
> 5 2 . (not estimable)
> 5 3 . (not estimable)
>
> I then do the -logit- estimtion without the -nonconst- option, and run the same -margins- command and get:
>
>
> Predictive margins Number of obs = 48
> Model VCE : OIM
>
> Expression : Pr(died), predict()
>
> 1._at : studytime = 10
>
> 2._at : studytime = 15
>
> 3._at : studytime = 20
>
> 4._at : studytime = 25
>
> 5._at : studytime = 30
>
> ------------------------------------------------------------------------------
> | Delta-method
> | Margin Std. Err. z P>|z| [95% Conf. Interval]
> -------------+----------------------------------------------------------------
> _at#drug |
> 1 1 | .9465649 .0518676 18.25 0.000 .8449063 1.048224
> 1 2 | .4488331 .149976 2.99 0.003 .1548854 .7427807
> 1 3 | .6152748 .182977 3.36 0.001 .2566464 .9739032
> 2 1 | .9333187 .0662422 14.09 0.000 .8034864 1.063151
> 2 2 | .3948395 .1327874 2.97 0.003 .1345811 .6550979
> 2 3 | .5688943 .1510893 3.77 0.000 .2727648 .8650238
> 3 1 | .9171489 .0877723 10.45 0.000 .7451183 1.089179
> 3 2 | .3431901 .1379768 2.49 0.013 .0727605 .6136197
> 3 3 | .5217416 .1263294 4.13 0.000 .2741405 .7693427
> 4 1 | .8975889 .1181116 7.60 0.000 .6660946 1.129083
> 4 2 | .2948301 .1565933 1.88 0.060 -.0120872 .6017474
> 4 3 | .4745012 .1173863 4.04 0.000 .2444282 .7045742
> 5 1 | .8741791 .1585532 5.51 0.000 .5634206 1.184938
> 5 2 | .2504701 .177148 1.41 0.157 -.0967337 .5976738
> 5 3 | .4278449 .1277973 3.35 0.001 .1773668 .6783231
> ------------------------------------------------------------------------------
>
> So clearly, the noconst is the issue here. You have not explained which command you are using for your fixed effects logistic estimation, so I am not sure why it is running the estimation without a constant. Could you be a little more specific about the command you are using?
>
> Best,
>
> Alfonso
>
> On Oct 31, 2013, at 10:29 AM, Nahla Betelmal <[email protected]> wrote:
>
>> Dear Statalist members,
>>
>> I am facing difficulty in getting the margins and plotting the
>> interaction graph in a fixed-effect logistic regression. I believe
>> this is due to the fact that fixed effect logistic regression does not
>> report an intercept. I wonder if there is a way to get around this to
>> produce the graph.
>>
>> In the regression there is three interactions ( Dummy variable with
>> Continuous variable in each interaction)
>>
>>
>> Conditional (fixed-effects) logistic regression Number of obs = 9941
>>
>> Wald chi2(34) = 681.92
>>
>> Prob > chi2 = 0.0000
>> Log pseudolikelihood = -3651.0306 Pseudo
>> R2 = 0.1458
>>
>> (Std. Err. adjusted for
>> 1220 clusters in firm)
>> ---------------------------------------------------------------------------------------------
>> | Robust
>> To | Coef. Std. Err. z P>|z|
>> [95% Conf. Interval]
>> ----------------------------+----------------------------------------------------------------
>> 1.DV | .1529853 .1576329 0.97 0.332
>> -.1559694 .4619401
>> |
>> DVr#c.IVA |
>> 0 | .1643871 .0829615 1.98 0.048
>> .0017855 .3269886
>> 1 | .2475583 .091258 2.71 0.007
>> .068696 .4264206
>> |
>> DV#c.IVB |
>> 0 | .1423918 .1179659 1.21 0.227
>> -.088817 .3736007
>> 1 | .4909195 .1660735 2.96 0.003
>> .1654214 .8164176
>> |
>> DVr#c.IVC |
>> 0 | .5103285 .104731 4.87 0.000
>> .3050596 .7155974
>> 1 | .5350398 .1325409 4.04 0.000
>> .2752644 .7948152
>>
>>
>> I tried to get each interaction alone first, but did not work
>>
>> . margins DV, at( IVA=(-1.1(0.1)1.7))
>> default predict option not appropriate with margins
>> r(322);
>>
>>
>> I tried all together
>>
>> . margins OC_2year, at((mean) IVA (mean) IVB (mean) IVC)
>> default predict option not appropriate with margins
>> r(322);
>>
>>
>> Many thanks in advance
>>
>> Nahla Betelmal
>> *
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>> * http://www.ats.ucla.edu/stat/stata/
>
>
> *
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*
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