AC_IPD_binY_contX

This data set contains simulated patient covariate and outcome values.

datasets

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

AC_IPD_binY_contX function

<div class="section" id="y-pf-cont-pf-cont-trt-trt-em-cont-em-cont-">
<h3><code>y ~ PF_cont_1 + PF_cont_2 + trt + trt:(EM_cont_1 + EM_cont_2)</code></h3>
<dl>
<dt>id</dt>
<dd>Numeric unique identifier</dd></dl><dt>PF_cont_1</dt>
<dd>Numeric prognostic factor continuous covariate</dd><dt>PF_cont_2</dt>
<dd>Numeric prognostic factor continuous covariate</dd><dt>EM_cont_1</dt>
<dd>Numeric effect modifier continuous covariate</dd><dt>EM_cont_2</dt>
<dd>Numeric effect modifier continuous covariate</dd><dt>trt</dt>
<dd>Factor treatment identifier. Levels A, C</dd><dt>y</dt>
<dd>Integer binary outcome</dd><dt>true_eta</dt>
<dd>Numeric linear predictor</dd>
</div>

Format

Individual-level patient data for binary outcome, continuous covariates — AC_IPD_binY_contX

<div class='section' id='y-pf-cont-pf-cont-trt-trt-em-cont-em-cont-'>
<h3><code>y ~ PF_cont_1 + PF_cont_2 + trt + trt:(EM_cont_1 + EM_cont_2)</code></h3>


<dl>
<dt>id</dt>
<dd>Numeric unique identifier</dd>

<dt>PF_cont_1</dt>
<dd>Numeric prognostic factor continuous covariate</dd>

<dt>PF_cont_2</dt>
<dd>Numeric prognostic factor continuous covariate</dd>

<dt>EM_cont_1</dt>
<dd>Numeric effect modifier continuous covariate</dd>

<dt>EM_cont_2</dt>
<dd>Numeric effect modifier continuous covariate</dd>

<dt>trt</dt>
<dd>Factor treatment identifier. Levels A, C</dd>

<dt>y</dt>
<dd>Integer binary outcome</dd>

<dt>true_eta</dt>
<dd>Numeric linear predictor</dd>


</dl>

</div>

AC_IPD_binY_contX: Individual-level patient data for binary outcome, continuous covariates

Description

Usage

Arguments

Format

`y ~ PF_cont_1 + PF_cont_2 + trt + trt:(EM_cont_1 + EM_cont_2)`

References