summary.outstandR

print.summary.outstandR

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

summary.outstandR function

<dl><dt>object</dt>
<dd><code>outstandR()</code> output object.</dd>
<dt>CI</dt>
<dd>Confidence interval level.</dd>
<dt>...</dt>
<dd>Additional arguments.</dd>
<dt>x</dt>
<dd>An object used to select a method.</dd>
<dt>digits</dt>
<dd>Minimal number of significant digits, see <code>print.default</code>.</dd></dl>

Arguments

Summary method for outstandR — summary.outstandR

<dl>

<dt>object</dt>
<dd><code>outstandR()</code> output object.</dd>


<dt>CI</dt>
<dd>Confidence interval level.</dd>


<dt>...</dt>
<dd>Additional arguments.</dd>


<dt>x</dt>
<dd>An object used to select a method.</dd>


<dt>digits</dt>
<dd>Minimal number of significant digits, see <code>print.default</code>.</dd>

</dl>

summary.outstandR: Summary method for outstandR

Description

Usage

Value

Arguments