simulated_data

Simulated dataset with an underlying Directed Graph structure for the metabolites.

datasets

The 'NetCoupler' algorithm identifies potential direct effects of
correlated, high-dimensional variables formed as a network with an external
variable. The external variable may act as the dependent/response variable
or as an independent/predictor variable to the network.

Luke Johnston

NetCoupler

Inference of Causal Links Between a Network and an External
Variable

Clemens Wittenbecher

Fabian Eichelmann

Helena Zacharias

Daniel Ibsen

simulated_data function

The simulated dataset is a <a rd-options="tibble:tibble-package" href="/link/tibble?package=NetCoupler&version=0.1.0&to=tibble%3Atibble-package" data-mini-rdoc="tibble:tibble-package::tibble">tibble</a> with the
following variables:<ul>
<li>Two outcome variables (<code>outcome_continuous</code> and <code>outcome_binary</code>) along
with survival time (<code>outcome_event_time</code>) that is used for the
<code>outcome_binary</code> variable</li>
<li>A generic <code>exposure</code> variable as continuous</li>
<li>12 <code>metabolite_*</code> variables</li>
<li>An <code>age</code> variable used as a confounder</li>
</ul>

Format

Simulated dataset with an underlying Directed Graph structure for the metabolites. — simulated_data

The simulated dataset is a <a rd-options='tibble:tibble-package' href='tibble'>tibble</a> with the
following variables:<ul>
<li>Two outcome variables (<code>outcome_continuous</code> and <code>outcome_binary</code>) along
with survival time (<code>outcome_event_time</code>) that is used for the
<code>outcome_binary</code> variable</li>
<li>A generic <code>exposure</code> variable as continuous</li>
<li>12 <code>metabolite_*</code> variables</li>
<li>An <code>age</code> variable used as a confounder</li>
</ul>

simulated_data: Simulated dataset with an underlying Directed Graph structure for the metabolites.

Description

Usage

Arguments

Format