What weights mean in WeightIt package

Question

I want to balance my data using the WeightIt package in R (method= ebal). I have used a code similar to the one below;

#Balancing covariates between treatment groups (binary)

W1 <- weightit(treat ~ age + educ + married + nodegree + re74, data = lalonde, method = "ebal", estimand = "ATT")

match.data(W1)

The outcome is my data table with an additional column called weights. What do those weights mean and how do I go on from here? (My next step would be to do a logit regression with a balanced dataset)

Thank you so much for helping!

Answer 1

weightit() estimates weights that, when applied to a dataset, yield balance in the treatment groups. To estimate effects in the weighted sample, include the weights in a regression of the outcome on the treatment. This is demonstrated in the WeightIt vignette.

You should not used match.data() with WeightIt. I'm not sure where you found the code to do that. match.data() is for use with MatchIt, which is a different package with its own functions. The fact that match.data() happened to work with WeightIt is unintended behavior and should not be relied on.

To estimate the effect of the treatment on a binary outcome (which I'll denote as Y in the code below and assume is in the lalonde dataset, even though in reality it is not), you would run the following after running the first line in your code above:

fit <- glm(Y ~ treat, data = lalonde, weights = W1$weights, family = binomial)
lmtest::coeftest(fit, vcov. = sandwich::vcovHC)

The coefficient on treat is the log odds ratio of the outcome.