QTE plots

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)