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Re: Re: st: psmatch2: ATT as percentage change using logs?
From
Nick Cox <[email protected]>
To
"[email protected]" <[email protected]>
Subject
Re: Re: st: psmatch2: ATT as percentage change using logs?
Date
Thu, 15 Aug 2013 16:18:12 +0100
Only Ubydul can be definitive on what was meant, but I think the only
link to your thread was that what is substantively a new thread was
started by replying to your post without deleting the contents or
changing the title.
But Lukas's post is further evidence for the underlying principle.
Sloppiness over posting just confuses people unnecessarily.
Nick
[email protected]
On 15 August 2013 16:10, Lukas Borkowski <[email protected]> wrote:
> I am a bit confused here. Ubydul, did you suggest to use a poisson regression (thanks Nick for spelling it out) to estimate the ATT in terms of a percentage change in the outcome variable?
>
> On 15.08.2013, at 16:06, Nick Cox <[email protected]> wrote:
>
>> The poison model sounds exactly right here, but do check your
>> presentation slides, paper drafts, etc. for this typo before going
>> public, otherwise even your friends will never let you hear the end of
>> this.
>>
>> You used a Poisson model.
>>
>> (Also, more fundamentally: Please don't start new threads by replying
>> to old ones _and without even changing the title\=, as is explained in
>> the FAQ.)
>>
>> Nick
>> [email protected]
>>
>>
>> On 15 August 2013 14:58, Ubydul Haque <[email protected]> wrote:
>>
>>> I used poison regression model to explore the association of indoor
>>> residual spraying (IRS) and long lasting insecticide treated net
>>> (LLIN) and malaria cases.
> #
> Lukas Borkowski
> University of London, School of Oriental and African Studies (SOAS)
>
> M: [email protected]
>
>
>
> On 15.08.2013, at 15:58, Ubydul Haque <[email protected]> wrote:
>
>>> Hello,
>>> I used poison regression model to explore the association of indoor
>>> residual spraying (IRS) and long lasting insecticide treated net
>>> (LLIN) and malaria cases. The outcome is the following:
>>> xi: xtpoisson totalcases pc_llin prop_irs i.year, irr exp(
>>> population) i( district_code) i.year
>>>
>>>
>>> ------------------------------------------------------------------------------
>>> malaria cases | IRR Std. Err. z P>|z| [95% Conf. Interval]
>>> -------------+----------------------------------------------------------------
>>> per capita_llin | 1.185207 .0483431 4.17 0.000
>>> 1.094145 1.283848
>>> proportion_irs | .7504642 .0696331 -3.09 0.002
>>> .6256765 .9001402
>>> _Iyear_2009 | .7955212 .0128567 -14.15 0.000
>>> .7707175 .8211232
>>> _Iyear_2010 | .6376188 .0165131 -17.38 0.000
>>> .6060614 .6708194
>>> _Iyear_2011 | .0790123 .0023992 -83.59 0.000
>>> .0744472 .0838574
>>> _Iyear_2012 | .013673 .0008019 -73.19 0.000
>>> .0121883 .0153386
>>> population | (exposure)
>>> -------------+----------------------------------------------------------------
>>> /lnalpha | 1.204061 .2083535 .7956957 1.612426
>>> -------------+----------------------------------------------------------------
>>> alpha | 3.333627 .6945728 2.215982 5.014964
>>> ------------------------------------------------------------------------------
>>> Likelihood-ratio test of alpha=0: chibar2(01) = 2.6e+04 Prob>=chibar2 = 0.000
>>>
>>> http://www.ats.ucla.edu/stat/stata/output/stata_poisson_output.htm
>>>
>>>
>>> The probable explanation is "An additional increase IRS in coverage by
>>> one percent will reduce malaria by a factor of XX (recalculate the
>>> 0.75 by using percentages rather than proportion), while holding LLINs
>>> in the model constant. On the other hand every additional ITN per
>>> capita will increase malaria by a factor of 1.19, while holding IRS in
>>> the model constant".
>>>
>>> Readers are interested to know the real impact of IRS and ITN to
>>> reduce malaria cases. But can I say like this "IRS coverage was
>>> associated with ....%/proportion/factor of reduced malaria prevalence
>>> while ITN was associated with %/proportion/factor of increased malaria
>>> prevalence".
>>>
>>> Thank you.
>>>
>>> Ubydul Haque
>>> Post Doctoral Fellow
>>> Johns Hopkins University
>>> 615, North Wolfe Street
>>> Baltimore, Maryland
>>> 21218, USA
>>>
>>> On Thu, Aug 15, 2013 at 9:25 AM, Lukas Borkowski <[email protected]> wrote:
>>>> Dear statalist,
>>>>
>>>> I am using the user-written command -psmatch2- (written by Leuven and Sianesi, 2003) to estimate the ATT of my participation variable on several outcome indicators. I am also using a DiD-regression approach to estimate the ATT where I transformed some of the indicators into logs to see the percentage change caused by the treatment. I wonder whether it is also reasonable to transform the outcome indicators into logs when running -psmatch2-. Can someone give me a quick hint? Thanks!
>>>>
>>>> Best, Lukas
>>>>
>>>> Leuven, E., and Sianesi, B. (2003) PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing. Available at: http://ideas.repec.org/c/boc/bocode/s432001.html
>>>>
>>>> #
>>>> Lukas Borkowski
>>>> University of London, School of Oriental and African Studies (SOAS)
>>>>
>>>> M: [email protected]
>>>>
>>>>
>>>>
>>>>
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>>>
>>>
>>>
>>> --
>>> Ubydul Haque
>>> Post Doctoral Fellow
>>> Johns Hopkins University
>>> 615, North Wolfe Street
>>> Baltimore, Maryland
>>> 21218, USA
>>>
>>> *
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>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>> * http://www.ats.ucla.edu/stat/stata/
>>
>
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