treat_model

Specifies the functional form and estimation engine for a treatment
previously specified by <code>set_treatment()</code>.

A set of functions to estimate the controlled direct effect of treatment fixing a potential mediator to a specific value. Implements the sequential g-estimation estimator described in Vansteelandt (2009) <doi:10.1097/EDE.0b013e3181b6f4c9> and Acharya, Blackwell, and Sen (2016) <doi:10.1017/S0003055416000216> and the telescope matching estimator described in Blackwell and Strezhnev (2020) <doi:10.1111/rssa.12759>.

Matthew Blackwell

DirectEffects

Estimating Controlled Direct Effects for Explaining Causal
Findings

Avidit Acharya

Maya Sen

Shiro Kuriwaki

Jacob Brown

Anton Strezhnev

treat_model function

<dl><dt>object</dt>
<dd>A <code>cde_estimator</code> object that contains output from a
previous call to <code>set_treatment()</code>.</dd>
<dt>formula</dt>
<dd>A formula specifying the design matrix of the
covariates. Passed to fitting engine or used with
<code><a href="/link/stats%3A%3Amodel.frame()?package=DirectEffects&version=0.3" data-mini-rdoc="DirectEffects::stats::model.frame()">stats::model.frame()</a></code> and <code><a href="/link/stats%3A%3Amodel.matrix()?package=DirectEffects&version=0.3" data-mini-rdoc="DirectEffects::stats::model.matrix()">stats::model.matrix()</a></code> to create the
design matrix for fitting engines that do not take formulas.</dd>
<dt>engine</dt>
<dd>String indicating the name of the fitting engine.</dd>
<dt>separate</dt>
<dd>Logical indicating whether the fitting algorithm
should be applied separately to each history of the treatment
variables up to this point (default) or not.</dd>
<dt>include_past</dt>
<dd>A logical value where <code>TRUE</code> indicates that
formulas passed to previous <code>treat_model</code> calls should be appended
to the formula given.</dd>
<dt>...</dt>
<dd>Other arguments to be passed to the engine algorithms.</dd></dl>

Arguments

Author

Specify the propensity score model for a CDE treatment — treat_model

<dl>

<dt>object</dt>
<dd>A <code>cde_estimator</code> object that contains output from a
previous call to <code>set_treatment()</code>.</dd>


<dt>formula</dt>
<dd>A formula specifying the design matrix of the
covariates. Passed to fitting engine or used with
<code><a href='https://rdrr.io/r/stats/model.frame.html'>stats::model.frame()</a></code> and <code><a href='https://rdrr.io/r/stats/model.matrix.html'>stats::model.matrix()</a></code> to create the
design matrix for fitting engines that do not take formulas.</dd>


<dt>engine</dt>
<dd>String indicating the name of the fitting engine.</dd>


<dt>separate</dt>
<dd>Logical indicating whether the fitting algorithm
should be applied separately to each history of the treatment
variables up to this point (default) or not.</dd>


<dt>include_past</dt>
<dd>A logical value where <code>TRUE</code> indicates that
formulas passed to previous <code>treat_model</code> calls should be appended
to the formula given.</dd>


<dt>...</dt>
<dd>Other arguments to be passed to the engine algorithms.</dd>

</dl>

treat_model: Specify the propensity score model for a CDE treatment

Description

Usage

Arguments

Author