rq.stat: rq.stat

In hettx: Fisherian and Neymanian Methods for Detecting and Measuring Treatment Effect Variation

rq.stat

Description

rq.stat is the Kolmogorov-smirnov statistic via quantile regression with covariates without further adjustment.

rq.stat.cond.cov does Kolmogorov-smirnov statistic via quantile regression with covariates, with a conditional approach; see Koenker and Xiao (2002).

rq.stat.uncond.cov implements a Kolmogorov-smirnov statistic via quantile regression with covariates, unconditional approach; see Firpo (2007).

Usage

rq.stat(Y, Z, rq.pts)

rq.stat.cond.cov(Y, Z, X, rq.pts)

rq.stat.uncond.cov(Y, Z, X, rq.pts)

Arguments

Y	Observed outcome vector
Z	Treatment assigment vector
rq.pts	Sequence of quantile points at which to evaluate the test. Default is seq(.1, .9, by = .1). Should not go beyond 0 and 1.
X	Additional pre-treatment covariates to adjust for in estimation, but not to interact with treatment.

Details

Warning: This function supresses all warnings of the 'rq()' method call.

Warning: This function supresses all warnings of the 'rq()' method call.

Value

The value of the test.

Examples

df <- make.randomized.dat( 1000, gamma.vec=c(1,1,1,2), beta.vec=c(-1,-1,1,0) )
rq.stat(df$Yobs, df$Z)

df <- make.randomized.dat( 1000, gamma.vec=c(1,1,1,2), beta.vec=c(-1,-1,1,0) )
rq.stat.cond.cov(df$Yobs, df$Z, df$A)

df <- make.randomized.dat( 1000, gamma.vec=c(1,1,1,2), beta.vec=c(-1,-1,1,0) )
rq.stat.uncond.cov(df$Yobs, df$Z, df$A)

hettx documentation built on Aug. 20, 2023, 1:06 a.m.