calculate_trial_mean_count

For the problem of indirect treatment comparison with limited subject-level data, this
package provides tools for model-based standardisation with several different computation approaches.
See Remiro‐Azócar A, Heath A, Baio G (2022) "Parametric G‐computation for compatible
indirect treatment comparisons with limited individual patient data",
Res. Synth. Methods, 1–31. ISSN 1759-2879, <doi:10.1002/jrsm.1565>.

Nathan Green

outstandR

Model-Based Standardisation for Indirect Treatment Comparison
with Limited Subject-Level Data

Chengyang Gao

Antonio Remiro-Azocar

calculate_trial_mean_count function

<dl><dt>ald</dt>
<dd>Aggregate level data. Data frame in long format.</dd>
<dt>tid</dt>
<dd>Treatment ID</dd>
<dt>effect</dt>
<dd>Effect name. String.</dd>
<dt>verbatim</dt>
<dd>Print messages, logical</dd></dl>

Arguments

Calculate Trial Mean Count Data — calculate_trial_mean_count

<dl>

<dt>ald</dt>
<dd>Aggregate level data. Data frame in long format.</dd>


<dt>tid</dt>
<dd>Treatment ID</dd>


<dt>effect</dt>
<dd>Effect name. String.</dd>


<dt>verbatim</dt>
<dd>Print messages, logical</dd>

</dl>

calculate_trial_mean_count: Calculate Trial Mean Count Data

Description

Usage

Value

Arguments