getESS

This function calculates the effective sample size for every dose group via the RBesT function ess().

Bayesian MCPMod (Fleischer et al. (2022)
<doi:10.1002/pst.2193>) is an innovative method that improves the
traditional MCPMod by systematically incorporating historical data,
such as previous placebo group data. This R package offers functions
for simulating, analyzing, and evaluating Bayesian MCPMod trials with
normally distributed endpoints. It enables the assessment of trial
designs incorporating historical data across various true
dose-response relationships and sample sizes. Robust mixture prior
distributions, such as those derived with the Meta-Analytic-Predictive
approach (Schmidli et al. (2014) <doi:10.1111/biom.12242>), can be
specified for each dose group. Resulting mixture posterior
distributions are used in the Bayesian Multiple Comparison Procedure
and modeling steps. The modeling step also includes a weighted model
averaging approach (Pinheiro et al. (2014) <doi:10.1002/sim.6052>).
Estimated dose-response relationships can be bootstrapped and
visualized.

Stephan Wojciekowski

BayesianMCPMod

Simulate, Evaluate, and Analyze Dose Finding Trials with
Bayesian MCPMod

Boehringer Ingelheim Pharma GmbH & Co. KG 

Lars Andersen

Jonas Schick

Sebastian Bossert

getESS function

<dl><dt>post_list</dt>
<dd>A posterior list object, for which the effective sample size for each dose group should be calculated</dd></dl>

Arguments

getESS — getESS

<dl>

<dt>post_list</dt>
<dd>A posterior list object, for which the effective sample size for each dose group should be calculated</dd>

</dl>

getESS: getESS

Description

Usage

Value

Arguments