WeightIt (version 0.12.0)

ESS: Compute effective sample size of weighted sample

Description

Computes the effective sample size (ESS) of a weighted sample, which represents the size of an unweighted sample with approximately the same amount of precision as the weighted sample under consideration.

Usage

ESS(w)

Arguments

w

a vector of weights

Details

The ESS is calculated as sum(w)^2/sum(w^2).

References

McCaffrey, D. F., Ridgeway, G., & Morral, A. R. (2004). Propensity Score Estimation With Boosted Regression for Evaluating Causal Effects in Observational Studies. Psychological Methods, 9(4), 403<U+2013>425. 10.1037/1082-989X.9.4.403

Shook-Sa, B. E., & Hudgens, M. G. (2020). Power and Sample Size for Marginal Structural Models. ArXiv:2003.05979 [Stat]. https://arxiv.org/abs/2003.05979

See Also

summary.weightit()

Examples

# NOT RUN {
library("cobalt")
data("lalonde", package = "cobalt")

#Balancing covariates between treatment groups (binary)
(W1 <- weightit(treat ~ age + educ + married +
                  nodegree + re74, data = lalonde,
                method = "ps", estimand = "ATE"))
summary(W1)
ESS(W1$weights[W1$treat == 0])
ESS(W1$weights[W1$treat == 1])
# }