Entropy balancing weights (Hainmueller, 2012) — morie_matching_entropy

Thin wrapper around WeightIt::weightit(method = "ebal") (or ebal::ebalance if WeightIt is unavailable). Computes weights for the control group so that the weighted moments of the covariates match those of the treated group.

Usage

morie_matching_entropy_balance(
  data,
  treatment,
  covariates,
  max_moment = 1L,
  max_iter = 500L,
  tol = 1e-06
)

Arguments

data: Data frame.
treatment: Binary treatment column name.
covariates: Character vector of covariates.
max_moment: Highest moment to balance (1 = means, 2 = means + var, 3 = + skewness).
max_iter: Maximum Newton iterations (forwarded to ebal).
tol: Convergence tolerance (forwarded to ebal).

Value

A numeric vector of weights aligned to the rows of data after dropping NAs. Treated units receive weight 1.

References

Hainmueller, J. (2012). Entropy balancing for causal effects. Political Analysis, 20(1), 25–46.

Examples

# \donttest{
set.seed(1)
df <- data.frame(y = rnorm(200), d = rbinom(200, 1, 0.4),
                 x1 = rnorm(200), x2 = rnorm(200))
w <- morie_matching_entropy_balance(df, "d", c("x1", "x2"))
# }