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

[thebudget72 m@iii@g oii gm@ii@com]

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.