Description Usage Arguments Details Value Author(s) See Also Examples
summary
method for class "ATE"
1 2 3 4 5 |
object |
An object of class |
x |
An object of class |
... |
Further arguments passed to or from methods. |
print.summary.ATE
prints a simplified output similar to print.summary.lm
. The resulting table provides the point estimates, estimated standard errors, 95% Wald confidence intervals, the Z-statistic and the P-values for a Z-test.
The function summary.ATE
returns a list with the following components
Estimate |
A matrix with point estimates along with standard errors, confidence intervals etc. This is the matrix users see with the |
vcov |
The variance-covariance matrix of the point estimates. |
Conv |
The convergence result of the |
weights |
The weights for each subject in each treatment arm. These are same as the |
call |
The |
Asad Haris, Gary Chan
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | library(ATE)
#binary treatment
set.seed(25)
n <- 200
Z <- matrix(rnorm(4*n),ncol=4,nrow=n)
prop <- 1 / (1 + exp(Z[,1] - 0.5 * Z[,2] + 0.25*Z[,3] + 0.1 * Z[,4]))
treat <- rbinom(n, 1, prop)
Y <- 200 + 10*treat+ (1.5*treat-0.5)*(27.4*Z[,1] + 13.7*Z[,2] +
13.7*Z[,3] + 13.7*Z[,4]) + rnorm(n)
X <- cbind(exp(Z[,1])/2,Z[,2]/(1+exp(Z[,1])),
(Z[,1]*Z[,3]/25+0.6)^3,(Z[,2]+Z[,4]+20)^2)
#estimation of average treatment effects (ATE)
fit1<-ATE(Y,treat,X)
summary(fit1)
#plot(fit1)
#estimation of average treatment effects on treated (ATT)
fit2<-ATE(Y,treat,X,ATT=TRUE)
summary(fit2)
#plot(fit2)
#three treatment groups
set.seed(25)
n <- 200
Z <- matrix(rnorm(4*n),ncol=4,nrow=n)
prop1 <- 1 / (1 + exp(1+Z[,1] - 0.5 * Z[,2] + 0.25*Z[,3] + 0.1 * Z[,4]))
prop2 <- 1 / (1 + exp(Z[,1] - 0.5 * Z[,2] + 0.25*Z[,3] + 0.1 * Z[,4]))
U <-runif(n)
treat <- numeric(n)
treat[U>(1-prop2)]=2
treat[U<(1-prop2)& U>(prop2-prop1)]=1
Y <- 210 + 10*treat +(27.4*Z[,1] + 13.7*Z[,2] +
13.7*Z[,3] + 13.7*Z[,4]) + rnorm(n)
X <- cbind(exp(Z[,1])/2,Z[,2]/(1+exp(Z[,1])),
(Z[,1]*Z[,3]/25+0.6)^3,(Z[,2]+Z[,4]+20)^2)
fit3<-ATE(Y,treat,X)
summary(fit3)
#plot(fit3)
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