example_surv

A data frame containing simulated data from a clinical trial
with a treatment arm (n=200) and a control arm (n=158), as well as data
from an external control (n=242).

datasets

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. 

example_surv function

A data frame with 600 rows and 6 variables:<dl>
<dt>trt</dt>
<dd>0/1, flag for treatment arm</dd><dt>ext</dt>
<dd>0/1, flag for external controls</dd><dt>eventtime</dt>
<dd>numeric &gt;0, survival time</dd><dt>status</dt>
<dd>0/1, event indicator</dd><dt>censor</dt>
<dd>0/1, censoring indicator</dd><dt>cov1</dt>
<dd>0/1, binary baseline covariate 1</dd><dt>cov2</dt>
<dd>integer in [0, 15], baseline covariate 2</dd><dt>cov3</dt>
<dd>continuous numeric, baseline covariate 3</dd>
</dl>

Format

Simulated Survival Data — example_surv

A data frame with 600 rows and 6 variables:<dl>
<dt>trt</dt>
<dd>0/1, flag for treatment arm</dd>

<dt>ext</dt>
<dd>0/1, flag for external controls</dd>

<dt>eventtime</dt>
<dd>numeric &gt;0, survival time</dd>

<dt>status</dt>
<dd>0/1, event indicator</dd>

<dt>censor</dt>
<dd>0/1, censoring indicator</dd>

<dt>cov1</dt>
<dd>0/1, binary baseline covariate 1</dd>

<dt>cov2</dt>
<dd>integer in [0, 15], baseline covariate 2</dd>

<dt>cov3</dt>
<dd>continuous numeric, baseline covariate 3</dd>


</dl>

Simulated Survival Data

example_surv: Simulated Survival Data

Description

Usage

Arguments

Format