natural_course

This function specifies the natural course intervention on the treatment variable in <code>data</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 

natural_course function

<dl><dt>data</dt>
<dd>a data frame containing the observed data.</dd>
<dt>treat_var</dt>
<dd>a string specifying the treatment variable in <code>data</code>.</dd></dl>

Arguments

Natural Course — natural_course

<dl>

<dt>data</dt>
<dd>a data frame containing the observed data.</dd>


<dt>treat_var</dt>
<dd>a string specifying the treatment variable in <code>data</code>.</dd>

</dl>

natural_course: Natural Course

Description

Usage

Value

Arguments

Examples