te_outcome_data-class

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 

te_outcome_data-class function

<dl>
<dt><code>data</code></dt>
<dd>A <code>data.table</code> object with columns "id", "period",</dd></dl>
<dt><code>n_rows</code></dt>
<dd>Number of rows</dd>
<dt><code>n_ids</code></dt>
<dd>Number of IDs</dd>
<dt><code>periods</code></dt>
<dd>Vector of periods
"treatment", "outcome", "eligible"</dd>

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TrialEmulation Outcome Data Class — te_outcome_data-class

<dl>
<dt><code>data</code></dt>
<dd>A <code>data.table</code> object with columns "id", "period",</dd>


<dt><code>n_rows</code></dt>
<dd>Number of rows</dd>


<dt><code>n_ids</code></dt>
<dd>Number of IDs</dd>


<dt><code>periods</code></dt>
<dd>Vector of periods
"treatment", "outcome", "eligible"</dd>


</dl>

TrialEmulation Outcome Data Class

te_outcome_data-class: TrialEmulation Outcome Data Class

Description

Arguments

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