cde_aipw: Initialize an AIPW CDE estimator

In mattblackwell/DirectEffects: Estimating Controlled Direct Effects for Explaining Causal Findings

Initialize an AIPW CDE estimator

Description

Initializes the specification of a CDE estimator based on an augmented inverse probability weighting approach.

Usage

cde_aipw(trim = c(0.01, 0.99), aipw_blip = TRUE)

Arguments

trim	A vector of length 2 indicating what quantiles of the propensity scores should be trimmed. By default this is c(0.01, 0.99) meaning that the top and bottom 1% of propensity scores are trunctated to these quantiles. If NULL, no trimming occurs.
aipw_blip	If TRUE (the default), augmented inverse probability weighting estimators will be used to estimate intermediate outcome regressions (blip functions).

mattblackwell/DirectEffects documentation built on Dec. 16, 2024, 6:14 p.m.