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BayesianMCPMod  

Simulate, Evaluate, and Analyze Dose Finding Trials with Bayesian MCPMod
View on CRAN: Click here


Download and install BayesianMCPMod package within the R console
Install from CRAN:
install.packages("BayesianMCPMod")

Install from Github:
library("remotes")
install_github("cran/BayesianMCPMod")

Install by package version:
library("remotes")
install_version("BayesianMCPMod", "1.0.1")



Attach the package and use:
library("BayesianMCPMod")
Maintained by
Stephan Wojciekowski
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-08
Latest Update: 2024-01-08
Description:
Bayesian MCPMod (Fleischer et al. (2022) ) 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) ), 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) ). Estimated dose-response relationships can be bootstrapped and visualized.
How to cite:
Stephan Wojciekowski (2024). BayesianMCPMod: Simulate, Evaluate, and Analyze Dose Finding Trials with Bayesian MCPMod. R package version 1.0.1, https://cran.r-project.org/web/packages/BayesianMCPMod. Accessed 29 Jan. 2025.
Previous versions and publish date:
1.0.0 (2024-01-08 17:50)
Other packages that cited BayesianMCPMod R package
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Other R packages that BayesianMCPMod depends, imports, suggests or enhances
Complete documentation for BayesianMCPMod
Functions, R codes and Examples using the BayesianMCPMod R package
Some associated functions: assessDesign . getBootstrapQuantiles . getContr . getCritProb . getESS . getModelFits . getPosterior . performBayesianMCP . performBayesianMCPMod . plot.modelFits . predict.modelFits . simulateData . 
Some associated R codes: BMCPMod.R . bootstrapping.R . modelling.R . plot.R . posterior.R . s3methods.R . simulation.R .  Full BayesianMCPMod package functions and examples
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