evalAugW: .evalAugW calls TMLE to use super learner to evalute...

In twoStageDesignTMLE: Targeted Maximum Likelihood Estimation for Two-Stage Study Design

.evalAugW calls TMLE to use super learner to evalute preliminary predictions for Q(0,W) and Q(1,W) conditioning on stage 1 covariates

Description

.evalAugW calls TMLE to use super learner to evalute preliminary predictions for Q(0,W) and Q(1,W) conditioning on stage 1 covariates

Usage

evalAugW(Y, A, W, Delta, id, family, SL.library)

Arguments

Y	outcome vector
A	binary treatment indicator
W	covariate matrix
Delta	outcome missingness indicator
id	identifier of i.i.d. unit
family	outcome regression family
SL.library	super learner library for outcome regression modeling

Value

W.Q, nx2 matrix of outcome predictions based on stage 1 covariates

twoStageDesignTMLE documentation built on Sept. 11, 2024, 6:38 p.m.