attbounds: Bounding the average treatment effect on the treated (ATT)

In ATbounds: Bounding Treatment Effects by Limited Information Pooling

Description

Bounds the average treatment effect on the treated (ATT) under the unconfoundedness assumption without the overlap condition.

Usage

attbounds(
  Y,
  D,
  X,
  rps,
  Q = 3L,
  studentize = TRUE,
  alpha = 0.05,
  x_discrete = FALSE,
  n_hc = NULL
)

Arguments

Y	n-dimensional vector of binary outcomes
D	n-dimensional vector of binary treatments
X	n by p matrix of covariates
rps	n-dimensional vector of the reference propensity score
Q	bandwidth parameter that determines the maximum number of observations for pooling information (default: Q = 3)
studentize	TRUE if X is studentized elementwise and FALSE if not (default: TRUE)
alpha	(1-alpha) nominal coverage probability for the confidence interval of ATE (default: 0.05)
x_discrete	TRUE if the distribution of X is discrete and FALSE otherwise (default: FALSE)
n_hc	number of hierarchical clusters to discretize non-discrete covariates; relevant only if x_discrete is FALSE. The default choice is n_hc = ceiling(length(Y)/10), so that there are 10 observations in each cluster on average.

Value

An S3 object of type "ATbounds". The object has the following elements.

call	a call in which all of the specified arguments are specified by their full names
type	ATT
cov_prob	Confidence level: 1-alpha
est_lb	estimate of the lower bound on ATT, i.e. E[Y(1) - Y(0) | D = 1]
est_ub	estimate of the upper bound on ATT, i.e. E[Y(1) - Y(0) | D = 1]
est_rps	the point estimate of ATT using the reference propensity score
se_lb	standard error for the estimate of the lower bound on ATT
se_ub	standard error for the estimate of the upper bound on ATT
ci_lb	the lower end point of the confidence interval for ATT
ci_ub	the upper end point of the confidence interval for ATT

References

Sokbae Lee and Martin Weidner. Bounding Treatment Effects by Pooling Limited Information across Observations.

Examples

  Y <- RHC[,"survival"]
  D <- RHC[,"RHC"]
  X <- RHC[,c("age","edu")]
  rps <- rep(mean(D),length(D))
  results_att <- attbounds(Y, D, X, rps, Q = 3)

ATbounds documentation built on Nov. 25, 2021, 1:06 a.m.