Re: st: obtaining confidence interval from -lincom-

[Tom <tommedema@gmail.com>]

That works just fine.

Thank you.

On Sat, May 25, 2013 at 3:59 PM, Federico Belotti <f.belotti@gmail.com> wrote:
> Tom,
>
> you can easily put -lincom- confidence interval into scalars using
>
> scalar ci_lb = r(estimate) + invnorm(0.025)*r(se)
>
> scalar ci_ub = r(estimate) + invnorm(0.975)*r(se)
>
> scalar list
>
> if the sample is small you could substitute invnormal() with invttail()
>
> Federico
>
> Il giorno 25/mag/2013, alle ore 15:04, Tom <tommedema@gmail.com> ha scritto:
>
>> Dear list,
>>
>> My research supervisor told me that I can generate a marginal effects
>> plot much like the one on page 14 of Brambor et al. (2006). [1]
>>
>> Note that using marginsplot in Stata 12 does not create such plot.
>> Therefore my supervisor told me to  do the following:
>>
>> ## code start ##
>>
>> * regress *
>> reg g ipr dtflog dtflogipr i.cid, robust
>>
>> cap drop l_dtf
>> cap drop l_est
>> gen l_dtflog = .
>> gen l_est = .
>>
>> * lincom *
>> forval i = 1/61 {
>>    local dtflog = (`i'-1) / 10
>>
>>    lincom _b[ipr] + `dtflog' * _b[dtflogipr], level(95)
>>
>>    * save *
>>    replace l_dtflog = `dtflog' in `i'
>>    replace l_est = r(estimate) in `i'
>>
>> }
>>
>> line l_est l_dtflog
>>
>> ## code end ##
>>
>> In short: the regression has two main independent variables ipr and
>> dtflog and one interaction term of these two variables (dtflogipr).
>> dtflog ranges from 0 to 6 and is looped through to see the interaction
>> effect for certain values of dtflog.
>>
>> I want to make the same graph as Brambor et al. (2006), where both
>> confidence interval borders being above or below the horizontal axis
>> indicates a singificant interaction effect.
>>
>> The only problem so far seems to be that while lincom returns a
>> confidence interval, when I do -return list- I only see the estimate
>> in r(estimate), but I cannot retrieve the confidence interval from the
>> list.
>>
>> So, how would I retrieve the confidence interval listed in the table
>> after running -lincom- ?
>>
>> Tom
>>
>> [1]: Brambor, Thomas, William Roberts Clark, and Matt Golder.
>> "Understanding interaction models: Improving empirical analyses."
>> Political analysis 14.1 (2006): 63-82.
>> Available from http://localgov.fsu.edu/readings_papers/Research%20Methods/Brambor_et_al_Multipolicative_Interactions.pdf
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>
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