R help - May 2021 - [MatchIt] Naive Estimator for ATT after Full Matching

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.

Do note, per the posting guide linked below (please read it if you haven't
done so already):

1. *"Questions about statistics:* The R mailing lists are primarily
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So do not be surprised if you do not get a response here.
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The matchit package maintainer can be found by: maintainer("matchit")
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you think the above applies.

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Wed, May 5, 2021 at 11:55 AM <thebudget72 at 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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> https://stat.ethz.ch/mailman/listinfo/r-help
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> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
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