weight

This function identifies the doubly robust ICE estimator. The treatment models could be specified by
<code>treat_model</code>.

Implements iterative conditional expectation (ICE) estimators of the plug-in g-formula (Wen, Young, Robins, and Hernán (2020) <doi: 10.1111/biom.13321>).
Both singly robust and doubly robust ICE estimators based on parametric models are available.
The package can be used to estimate survival curves under sustained treatment strategies (interventions) using longitudinal data with time-varying treatments, time-varying confounders, censoring, and competing events.
The interventions can be static or dynamic, and deterministic or stochastic (including threshold interventions). Both prespecified and user-defined interventions are available.

Jing Li

gfoRmulaICE

Parametric Iterative Conditional Expectation G-Formula

Zhaoxi Cheng

Sophia Rein

Ryan O'Dea

Sean McGrath

Lan Wen

Miguel A. Hernán

2024 The President and Fellows of Harvard College 

weight function

<dl><dt>treat_model</dt>
<dd>a list of formulas specifying the treatment model for the corresponding treatment variable. The length of list must match
the number of treatment variables.</dd></dl>

Arguments

Indicator for the doubly robust ICE estimator — weight

<dl>

<dt>treat_model</dt>
<dd>a list of formulas specifying the treatment model for the corresponding treatment variable. The length of list must match
the number of treatment variables.</dd>

</dl>

weight: Indicator for the doubly robust ICE estimator

Description

Usage

Value

Arguments