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Re: st: RE: Re: estout


From   Yuesheng Wu <[email protected]>
To   [email protected]
Subject   Re: st: RE: Re: estout
Date   Wed, 12 Mar 2014 00:46:10 -0400

Hi Nick,
   That is a very good point; here is the example I can come up with:
sysuse auto
poisson price weight mpg

estout, cells(b se) transform(weight
exp(_b[weight]+_b[mpg])-exp(_b[weight])
exp(_b[weight]+_b[mpg])-exp(_b[weight]) mpg
exp(_b[weight]+_b[mpg])-exp(_b[weight]) exp(_b[weight]+_b[mpg]))


Here, I want to calculate the term
"exp(_b[weight]+_b[mpg])-exp(_b[weight]) "; the STATA gives the
following results:

        b/se
price
weight  -.0123634
        -1.000255
mpg     -.0123634
        .0004759
_cons   8.179377
        .0194376

Note that the standard error is -1.000255.

Any thoughts?

Thanks a lot!

Yuesheng

On Tue, Mar 11, 2014 at 2:18 PM, Nick Cox <[email protected]> wrote:
> No doubt, but you are still not giving any details of the code you used.
>
> How can users of -estout- (SSC) (not me, by the way) explain whether
> you messed up your code when you don't even say what it is!
>
> A reproducible example -- one based on a dataset we can all access --
> would be even better.
>
> Nick
> [email protected]
>
> Yuesheng Wu
>
>>     Thanks for your help.
>>     I did not export the estimation results to Excel: I just did
>> everything in Stata.
>
>  On Tue, Mar 11, 2014 at 1:32 PM, Rubil Ivica <[email protected]> wrote:
>
>>> you are probably exporting your results to Excel, right? If so, then you
>>> need either of the following two options: "nopa" or "brackets".
>>> The problem is that estout by default puts standard errors in
>>> parentheses (std.err.) and when this is exported to Excel, it becomes
>>> -std.err. This
>>> is a convention in accounting that instead od negative values those are
>>> put in parentheses. "nopa" will drop parentheses, and "brackets" will
>>> put
>>> berackets [...] instead of parentheses (...). Hopefully this helps.
>
> Yuesheng Wu
>
>>>   After I run the Poisson regression by "poisson", I use to estout to
>>> calculate standard error of a term with the estimates of two parameters;
>>> it turns out the standard error is negative. I am just wondering whether
>>> the estout only works for one parameter; or I mess up with the code.
>>>
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