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Re: st: predict after logit
From
Sara Borelli <[email protected]>
To
[email protected]
Subject
Re: st: predict after logit
Date
Thu, 12 Jul 2012 14:08:10 -0400
thank you Tim for the suggestion,
I cannot find the margins options...may it be because this is a new
feature of STATA ?
I am using stata 10
thanks
Sara
On Wed, Jul 11, 2012 at 5:27 PM, Tim Wade <[email protected]> wrote:
> apologies, the first segment of code should read:
>
> sysuse auto.dta
> xtile hiprice=price, nq(2)
> logistic foreign hiprice mpg
> margins, by(hiprice)
>
>
> On Wed, Jul 11, 2012 at 5:26 PM, Tim Wade <[email protected]> wrote:
>> If I understand what you are asking, I think margins does this:
>>
>> margins, by(hiprice)
>> sysuse auto.dta
>> xtile hiprice=price, nq(2)
>> logistic foreign hiprice mpg
>> margins, by(hiprice)
>>
>>
>> ------------------------------------------------------------------------------
>> | Delta-method
>> | Margin Std. Err. z P>|z| [95% Conf. Interval]
>> -------------+----------------------------------------------------------------
>> hiprice |
>> 1 | .2162162 .0557663 3.88 0.000 .1069163 .3255161
>> 2 | .3783784 .0681487 5.55 0.000 .2448094 .5119474
>> ------------------------------------------------------------------------------
>>
>>
>> note this margin estimates are the same as the means of phat:
>>
>> logistic foreign hiprice mpg
>> predict phat
>> tabulate hiprice, summ(phat)
>>
>>
>> 2 quantiles | Summary of Pr(foreign)
>> of price | Mean Std. Dev. Freq.
>> ------------+------------------------------------
>> 1 | .21621622 .23645819 37
>> 2 | .37837838 .25520846 37
>> ------------+------------------------------------
>> Total | .2972973 .25759862 74
>>
>> Tim
>>
>>
>> On Wed, Jul 11, 2012 at 1:01 PM, Sara Borelli <[email protected]> wrote:
>>> Hi all,
>>> I am running a logit model to obtain a predicted probability for each
>>> individual (phat_i) using predict, pr command .
>>>
>>> I have to calculate the average of this prediction within some
>>> categories of a variable x:
>>> mean_phat_i=mean( phat_i) by(x)
>>> and obtain standard errors and confidence interval for this mean.
>>>
>>> I know I can use adjust for this purpose, but I also need to calculate
>>> standard errors/confidence intervals for mean_phat_i
>>>
>>> Thanks in advance for any insight
>>>
>>> Sara
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