estforboot: estforboot

In shuyang1987/IntegrativeHTE: Integrative analysis of the heterogeneous treatment effect (HTE)

Description

A function computes the bootstrap statistics.

Usage

estforboot(A.t, X.t, Y.t, A.os, X.os, Y.os, n.t, m, cnames, family.oc,
  nptb, gamma1, gamma2)

Arguments

A.t	is a vector of treatment ( n x 1).
X.t	is a matrix of covariates without intercept ( n x p).
Y.t	is a vector of outcome ( n x 1).
A.os	is a vector of treatment ( m x 1).
X.os	is a matrix of covariates without intercept ( m x p).
Y.os	is a vector of outcome ( m x 1).
n.t	is the RT sample size.
m	is the RW sample size.
cnames	is the names for the estimators.
family.oc	specifies the family for the outcome model. "gaussian": a linear regression model for the continuous outcome. "binomial": a logistic regression model for the binary outcome.
nptb	is the number for replication-based method for estimating Sigma_SS.
gamma1	is the parameter in the violation test such that T > chisq_1-gamma1 indicates the bias of the RW analysis is significant.
gamma2	is a smooth parameter in using the normal cummulative distribution with mean 0 and variance gamma2^2 function to approximate the indicator function.

Value

the boostrap statistics

shuyang1987/IntegrativeHTE documentation built on April 13, 2020, 1:43 a.m.