calculate_predictions

Calculate and transform predictions

internal

Implements target trial emulation methods to apply randomized
clinical trial design and analysis in an observational setting. Using
marginal structural models, it can estimate intention-to-treat and
per-protocol effects in emulated trials using electronic health
records. A description and application of the method can be found in
Danaei et al (2013) <doi:10.1177/0962280211403603>.

Isaac Gravestock

TrialEmulation

Causal Analysis of Observational Time-to-Event Data

Li Su

Roonak Rezvani

Julia Moesch

Medical Research Council (MRC) 

F. Hoffmann-La Roche AG 

calculate_predictions function

<dl><dt>newdata</dt>
<dd>New data to predict outcome</dd>
<dt>model</dt>
<dd>GLM object</dd>
<dt>treatment_values</dt>
<dd>Named vector of value to insert into <code>assigned_treatment</code> column</dd>
<dt>pred_fun</dt>
<dd>Function to transform prediction matrix</dd>
<dt>coefs_mat</dt>
<dd>Matrix of coefficients corresponding to <code>model_matrix</code>.</dd>
<dt>matrix_n_col</dt>
<dd>Expected number of column after prediction.</dd></dl>

Arguments

Calculate and transform predictions — calculate_predictions

<dl>

<dt>newdata</dt>
<dd>New data to predict outcome</dd>


<dt>model</dt>
<dd>GLM object</dd>


<dt>treatment_values</dt>
<dd>Named vector of value to insert into <code>assigned_treatment</code> column</dd>


<dt>pred_fun</dt>
<dd>Function to transform prediction matrix</dd>


<dt>coefs_mat</dt>
<dd>Matrix of coefficients corresponding to <code>model_matrix</code>.</dd>


<dt>matrix_n_col</dt>
<dd>Expected number of column after prediction.</dd>

</dl>

calculate_predictions: Calculate and transform predictions

Description

Usage

Value

Arguments