EstGATE {MatchGATE}

Estimating Group Average Treatment Effects

Description

When imputed values for Y^1 and Y^0 are available for each individual, we can use EstGATE to estimate the group average treatment effects (GATE) defined by

GATE(z) = E[Y^1 - Y^0 | Z=z]

for some for possible values z of Z.

Usage

EstGATE(Y1_Y0, Z, Zeval, h)

Arguments

Y1_Y0

A vector in which each element is a treatment effect for each individual.

Z

A subvector of the covariates X, which is used to define the subgroup of interest.

Zeval

Vector of evaluation points of Z.

h

A smoothing parameter, bandwidth.

Value

The value of the corresponding GATE at different evaluation points.

Examples

set.seed(691)
n <- 2000
X1 <- runif(n, -0.5,0.5)
X2 <- rnorm(n, sd = 0.5)
X = cbind(X1, X2)
A = sample(c(0,1), n, TRUE)
Y0 <- X2 + X1*X2/2 + rnorm(n, sd = 0.25)
Y1 <- A * (2*X1^2) + X2 + X1*X2/2 + rnorm(n, sd = 0.25)
Y <- A * Y1 + (1-A)*Y0
res.match <- match_y1y0(X, A, Y, K = 5)
y1_y0 <- res.match$Y1 - res.match$Y0
Z <- X1
Zeval = seq(min(Z), max(Z), len = 101)
h <- 0.5 * n^(-1/5)
res <- EstGATE(Y1_Y0 = y1_y0, Z, Zeval, h = h)
plot(x = Zeval, y = 2*Zeval^2,
     type = "l", xlim = c(-0.6, 0.5),
     main = "Estimated value vs. true value",
     xlab = "Zeval", ylab = "GATE",
     col = "DeepPink", lwd = "2")
lines(x = res$Zeval, y = res$GATE,
      col="DarkTurquoise", lwd = "2")
legend('bottomleft', c("Estimated GATE","True GATE"),
       col=c("DarkTurquoise","DeepPink"),
       text.col=c("DarkTurquoise","DeepPink"), cex = 0.8)