aihuman (version 1.0.0)

BootstrapAPCEipw: Bootstrap for estimating variance of APCE

Description

Estimate variance of APCE for frequentist analysis using bootstrap. See S7 for more details.

Usage

BootstrapAPCEipw(data, rep = 1000)

Value

An object of class list with the following elements:

P.D1.boot

An array with dimension rep by (k+1) by (k+2) for quantity P(D(1)=d| R=r), dimension 1 is rep (size of bootstrap), dimension 2 is (k+1) values of D from 0 to k, dimension 3 is (k+2) values of R from 0 to k+1.

P.D0.boot

An array with dimension rep by (k+1) by (k+2) for quantity P(D(0)=d| R=r).

APCE.boot

An array with dimension rep by (k+1) by (k+2) for quantity P(D(1)=d| R=r)-P(D(0)=d| R=r).

P.R.boot

An array with dimension rep by (k+2) for quantity P(R=r) for r from 0 to (k+1).

alpha.boot

An array with estimated alpha for each bootstrap.

delta.boot

An array with estimated delta for each bootstrap.

Arguments

data

A data.frame or matrix of which columns consists of pre-treatment covariates, a binary treatment (Z), an ordinal decision (D), and an outcome variable (Y). The column names of the latter three should be specified as "Z", "D", and "Y" respectively.

rep

Size of bootstrap

Examples

data(synth)
set.seed(123)
boot_apce <- BootstrapAPCEipw(synth, rep = 100)