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Re: st: series of teffects on multiple outcomes


From   László Sándor <[email protected]>
To   [email protected]
Subject   Re: st: series of teffects on multiple outcomes
Date   Fri, 6 Sep 2013 19:06:29 -0400

Thanks, Billy. I am not sure that the same applies to multivalued
treatments following Cattaneo (2010). And of course, the built-in code
is much faster — though it looks like it need to be rerun.

Thanks!

On Fri, Sep 6, 2013 at 6:12 PM, William Buchanan
<[email protected]> wrote:
> You should be able to do this with some of the user-written PSM/PSA programs.  Additionally, you could always do things manually; there are examples on the UCLA website for Murnane, R. J., & Willett, J. B. (2010) Methods matter: Improving causal inference in education and social science. New York City, NY: Oxford University Press.
>
> HTH,
> Billy
>
> Sent from my iPhone
>
> On Sep 6, 2013, at 15:51, László Sándor <[email protected]> wrote:
>
>> Hi,
>>
>> I wonder if I could make it faster to -teffects aipw- multiple outcome
>> variables one after another. If I am correct, the regression
>> adjustment need to be rerun for different outcomes, but the treatment
>> prediction need not be. Is there a way to leverage one run for
>> another?
>>
>> What I have in mind is, in "pseudocode":
>>
>> teffects aipw (outcome1 controls) (multilevel_treatment predictors), SAVEPW
>> teffects aipw (outcome1 controls) (), USEPW
>>
>> Thanks,
>>
>> Laszlo
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