oneStepATT: Calculate Additive treatment effect among the treated...

In tmle: Targeted Maximum Likelihood Estimation

Calculate Additive treatment effect among the treated (oneStepATT)

Description

An internal function called by the tmle function to calculate the additive treatment effect among the treated (ATT) using a universal least favorable submodel (on the transformed scale if outcomes are continuous). The function is called a second time with updated arguments to calculate the additive treatment effect among the controls (ATC). Missingness in the outcome data is allowed.

Usage

oneStepATT(Y, A, Delta, Q, g1W, pDelta1, depsilon, max_iter, gbounds, Qbounds, obsWeights)

Arguments

Y	continuous or binary outcome variable
A	binary treatment indicator, 1 - treatment, 0 - control
Delta	indicator of missing outcome. 1 - observed, 0 - missing
Q	a 3-column matrix (Q(A,W), Q(1,W), Q(0,W))
g1W	treatment mechanism estimates, P(A=1|W)
pDelta1	censoring mechanism estimates, a 2-column matrix [P(Delta=1|A=0,W), P(Delta=1|A=1,W)]
depsilon	step size for delta moves, set to 0.001
max_iter	maximum number of iterations before terminating without convergence
gbounds	bounds on the propensity score for untreated subjects
Qbounds	alpha bounds on the logit scale
obsWeights	sampling weights

Value

psi	effect estimate (on the transformed scale for continuous outcomes)
IC	influence function
conv	TRUE if procedure converged, FALSE otherwise

Author(s)

Susan Gruber

See Also

tmle,

tmle documentation built on Aug. 23, 2023, 1:08 a.m.