SimDataList-class

.sim_data_list

A class for defining generated data for use as part of a
simulation study. Objects of class <code>SimDataList</code> should not be created
directly but by the constructor <code>sim_data_list()</code>.

Bayesian dynamic borrowing is an approach to incorporating external
data to supplement a randomized, controlled trial analysis in which
external data are incorporated in a dynamic way (e.g., based on similarity
of outcomes); see Viele 2013 <doi:10.1002/pst.1589> for an overview.
This package implements the hierarchical commensurate prior approach to dynamic borrowing
as described in Hobbes 2011 <doi:10.1111/j.1541-0420.2011.01564.x>.
There are three main functionalities. First, 'psborrow2' provides a user-friendly
interface for applying dynamic borrowing on the study results handles the Markov Chain
Monte Carlo sampling on behalf of the user. Second, 'psborrow2' provides a
simulation framework to compare different borrowing parameters (e.g. full borrowing, no
borrowing, dynamic borrowing) and other trial and borrowing characteristics
(e.g. sample size, covariates) in a unified way. Third, 'psborrow2' provides
a set of functions to generate data for simulation studies, and also allows
the user to specify their own data generation process. This package is designed to
use the sampling functions from 'cmdstanr' which can be installed from
<https://stan-dev.r-universe.dev>.

Matt Secrest

psborrow2

Bayesian Dynamic Borrowing Analysis and Simulation

Isaac Gravestock

Craig Gower-Page

Manoj Khanal

Mingyang Shan

Kexin Jin

Zhi Yang

Genentech, Inc. 

SimDataList-class function

<dl>
<dt><code>data_list</code></dt>
<dd>list of lists of matrices. The lists at the highest
level differ in that the parameters used to generate the data. The matrices
at lowest level are different iterations of the same data generation
parameters.</dd></dl>
<dt><code>guide</code></dt>
<dd>data.frame. <code>guide</code> contains information on the parameters
that differ at the highest level of <code>data_list</code>.</dd>
<dt><code>effect</code></dt>
<dd>character. The column in <code>guide</code> that
corresponds to the true treatment effect estimate (hazard ratio or odds ratio).</dd>
<dt><code>drift</code></dt>
<dd>character. The column in <code>guide</code> that
corresponds to the drift between external and internal control arms. A
drift &gt;1 means the external arm experiences greater effects.</dd>
<dt><code>index</code></dt>
<dd>character. The column in <code>guide</code> that corresponds
to the index of the parameter situations in <code>data_list</code>.</dd>

Slots

SimDataList Class — SimDataList-class

<dl>
<dt><code>data_list</code></dt>
<dd>list of lists of matrices. The lists at the highest
level differ in that the parameters used to generate the data. The matrices
at lowest level are different iterations of the same data generation
parameters.</dd>


<dt><code>guide</code></dt>
<dd>data.frame. <code>guide</code> contains information on the parameters
that differ at the highest level of <code>data_list</code>.</dd>


<dt><code>effect</code></dt>
<dd>character. The column in <code>guide</code> that
corresponds to the true treatment effect estimate (hazard ratio or odds ratio).</dd>


<dt><code>drift</code></dt>
<dd>character. The column in <code>guide</code> that
corresponds to the drift between external and internal control arms. A
drift &gt;1 means the external arm experiences greater effects.</dd>


<dt><code>index</code></dt>
<dd>character. The column in <code>guide</code> that corresponds
to the index of the parameter situations in <code>data_list</code>.</dd>


</dl>

<code>SimDataList</code> Class

SimDataList-class: `SimDataList` Class

Description

Arguments

Slots