plot.qte: QTE plots

In QTE.RD: Quantile Treatment Effects under the Regression Discontinuity Design

QTE plots

Description

plot.qte generates plots summarizing the QTE estimates and their uniform confidence bands, helping users visualize the results. It also makes plots for conditional quantile processes for each side of the cutoff.

Usage

## S3 method for class 'qte'
plot(x, ptype = 1, ytext = NULL, mtext = NULL, subtext = NULL, ...)

Arguments

x	an object of class qte or summary.qte produce by rd.qte.
ptype	either 1 or 2. Set ptype=1 for the QTE plots, and ptype=2 for the conditional quantile plots. The default value is 1.
ytext	the y-axis label.
mtext	the title of the plot.
subtext	the subtitles (used for the conditional quantile plots only).
...	optional arguments to plot

Value

plot(s) of the QTE estimates and uniform confidence bands.

Examples

# Without covariate
n = 500
x = runif(n,min=-4,max=4)
d = (x > 0)
y = x + 0.3*(x^2) - 0.1*(x^3) + 1.5*d + rnorm(n)
tlevel = seq(0.1,0.9,by=0.1)
A <- rd.qte(y=y,x=x,d=d,x0=0,z0=NULL,tau=tlevel,bdw=2,bias=1)
plot(A)

y.text = "test scores"
m.text = "QTE and Uniform band"
plot(A,ytext=y.text,mtext=m.text)

A2 <- summary(A,alpha=0.1)
plot(A2)

z = sample(c(0,1),n,replace=TRUE)
y = x + 0.3*(x^2) - 0.1*(x^3) + 1.5*d + d*z + rnorm(n)
A <- rd.qte(y=y,x=cbind(x,z),d=d,x0=0,z0=c(0,1),tau=tlevel,bdw=2,bias=1)
A2 <- summary(A,alpha=0.1)

y.text = "test scores"
m.text = c("D=0","D=1")
plot(A2,ytext=y.text,mtext=m.text)

# conditional quantile plots
n = 500
x = runif(n,min=-4,max=4)
d = (x > 0)
y = x + 0.3*(x^2) - 0.1*(x^3) + 1.5*d + rnorm(n)
tlevel = seq(0.1,0.9,by=0.1)
A <- rd.qte(y=y,x=x,d=d,x0=0,z0=NULL,tau=tlevel,bdw=2,bias=1)
A2 <- summary(A,alpha=0.1)

y.text = "test scores"
m.text = "Conditional quantile functions"
sub.text = c("D=0 group","D=1 group")
plot(A2,ptype=2,ytext=y.text,mtext=m.text,subtext=sub.text)

QTE.RD documentation built on Aug. 30, 2025, 9:06 a.m.