[R] [MatchIt] Naive Estimator for ATT after Full Matching

Bert Gunter bgunter@4567 @end|ng |rom gm@||@com
Wed May 5 22:07:41 CEST 2021

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On Wed, May 5, 2021 at 11:55 AM <thebudget72 using gmail.com> wrote:

> Dear R-help ML,
> I would like to compute a Naive Estimator for the Average Treatment
> Effect (ATT) after a Propensity Score Matching with full matching.
> Since it is full matching, the resulting post-matching database contains
> all the observations of the original dataset.
> I came up with this code, which does a weighted average of the outcomes,
> using the weights provided by the matching process, but I'm not sure
> this is the correct way to achieve it.
> How can I compute the ATT using a Naive Estimator after PSM?
> I know I am supposed to do a regression, but I am interested in
> computing a Naive Estimator as a difference between the means across the
> two groups.
> ```r
> library("MatchIt")
> data("lalonde")
> m.out2 <- matchit(treat ~ age + educ + race + married +
>                    nodegree + re74 + re75,
>                    data = lalonde,
>                    method = "full",
>                    distance = "glm",
>                    link = "probit")
> m.data2 <- match.data(m.out2)
> te <- weighted.mean(m.data2$re78[m.data2$treat],
>                      m.data2$weights[m.data2$treat])
> nte <- weighted.mean(m.data2$re78[!m.data2$treat],
>                       m.data2$weights[!m.data2$treat])
> ne2w <- round(te-nte, 2)
> print(paste0("The ATT estimated with a NE is: ", ne2w))
> ```
> Thanks in advance and best regards.
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