quant_est: Estimate the Marginal Quantile Given a Specific Treatment...

In quantoptr: Algorithms for Quantile- And Mean-Optimal Treatment Regimes

Description

Estimate the marginal quantile if the entire population follows a treatment regime indexed by the given parameters. This function supports the qestimate function.

Usage

quant_est(beta, x, y, a, prob, tau)

Arguments

beta	a vector indexing the treatment regime. It indexes a linear treatment regime: d(x)= I{β_0 + β_1*x_1 + ... + β_k*x_k > 0}.
x	a matrix of observed covariates from the sample. Notice that we assumed the class of treatment regimes is linear. This is important that columns in x matches with beta.
y	a vector, the observed responses from a sample
a	a vector of 0s and 1s, the observed treatments from a sample
prob	a vector, the propensity scores of getting treatment 1 in the samples
tau	a numeric value between 0 and 1. The quantile level of interest.

quantoptr documentation built on May 2, 2019, 4:03 p.m.