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Re: Re: st: psmatch2: ATT as percentage change using logs?
From
Lukas Borkowski <[email protected]>
To
[email protected]
Subject
Re: Re: st: psmatch2: ATT as percentage change using logs?
Date
Thu, 15 Aug 2013 17:10:02 +0200
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]
>>>
>>>
>>>
>>>
>>> *
>>> * For searches and help try:
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>>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>>> * http://www.ats.ucla.edu/stat/stata/
>>
>>
>>
>> --
>> Ubydul Haque
>> Post Doctoral Fellow
>> Johns Hopkins University
>> 615, North Wolfe Street
>> Baltimore, Maryland
>> 21218, USA
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/faqs/resources/statalist-faq/
>> * http://www.ats.ucla.edu/stat/stata/
>
*
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