Sim.Data.STS

The function <code>Sim.Data.STS</code> simulates a dataset that contains the variables Treat, Surr, True, and Pat.ID. The user can specify the total number of patients, the desired \(R_{indiv}\) value (also referred to as the adjusted association (\(\gamma\)) in the single-trial meta-analytic setting), and the desired means of the surrogate and the true endpoints in the experimental and control treatment groups.

Simulate data

Single-trial setting

In a clinical trial, it frequently occurs that the most credible
outcome to evaluate the effectiveness of a new therapy (the true endpoint) is
difficult to measure. In such a situation, it can be an effective strategy to
replace the true endpoint by a (bio)marker that is easier to measure and that
allows for a prediction of the treatment effect on the true endpoint (a
surrogate endpoint). The package 'Surrogate' allows for an evaluation of the
appropriateness of a candidate surrogate endpoint based on the meta-analytic,
information-theoretic, and causal-inference frameworks. Part of this software
has been developed using funding provided from the European Union's Seventh
Framework Programme for research, technological development and demonstration
(Grant Agreement no 602552), the Special Research Fund (BOF) of Hasselt
University (BOF-number: BOF2OCPO3), GlaxoSmithKline Biologicals, Baekeland
Mandaat (HBC.2022.0145), and Johnson & Johnson Innovative Medicine.

Wim der Elst

Surrogate

Evaluation of Surrogate Endpoints in Clinical Trials

Wim Van Der Elst

Florian Stijven

Fenny Ong

Paul Meyvisch

Alvaro Poveda

Ariel Alonso

Hannah Ensor

Christoper Weir

Geert Molenberghs

Sim.Data.STS function

<dl> <dt>N.Total</dt>
<dd>The total number of patients in the simulated dataset. Default \(2000\).</dd> <dt>R.Indiv.Target</dt>
<dd>The desired \(R_{indiv}\) (or \(\gamma\)) value in the simulated dataset. Default \(0.80\).</dd> <dt>Means</dt>
<dd>A vector that specifies the desired mean for the surrogate in the control treatment group, mean for the surrogate in the experimental treatment group, mean for the true endpoint in the control treatment group, and mean for the true endpoint in the experimental treatment group, respectively. Default <code>c(0, 0, 0, 0)</code>.</dd> <dt>Seed</dt>
<dd>The seed that is used to generate the dataset. Default <code>sample(x=1:1000, size=1)</code>, i.e., a random number between 1 and 1000.</dd></dl>

Arguments

Wim Van der Elst, Ariel Alonso, &amp; Geert Molenberghs

Author

Simulates a dataset that can be used to assess surrogacy in the single-trial setting — Sim.Data.STS

<dl>

 <dt>N.Total</dt>
<dd>The total number of patients in the simulated dataset. Default \(2000\).</dd>

 <dt>R.Indiv.Target</dt>
<dd>The desired \(R_{indiv}\) (or \(\gamma\)) value in the simulated dataset. Default \(0.80\).</dd>

 <dt>Means</dt>
<dd>A vector that specifies the desired mean for the surrogate in the control treatment group, mean for the surrogate in the experimental treatment group, mean for the true endpoint in the control treatment group, and mean for the true endpoint in the experimental treatment group, respectively. Default <code>c(0, 0, 0, 0)</code>.</dd>

 <dt>Seed</dt>
<dd>The seed that is used to generate the dataset. Default <code>sample(x=1:1000, size=1)</code>, i.e., a random number between 1 and 1000.</dd>

</dl>

Simulates a dataset that can be used to assess surrogacy in the single-trial setting

Sim.Data.STS: Simulates a dataset that can be used to assess surrogacy in the single-trial setting

Description

Usage

Arguments

Author

Details

See Also

Examples