baymedr: An R Package and Web Application for the Calculation of Bayes Factors for Superiority, Equivalence, and Non-Inferiority Designs

TL;DR

baymedr is an R package and web app that facilitates Bayesian analysis of clinical trial designs, offering an alternative to traditional frequentist methods for superiority, equivalence, and non-inferiority testing.

Contribution

It introduces baymedr, a user-friendly tool for calculating Bayes factors in clinical trial design analysis, addressing limitations of frequentist approaches.

Findings

Provides a practical tool for Bayesian hypothesis testing in clinical trials.

Enables reanalysis of existing trial data using Bayes factors.

Improves interpretability of statistical evidence in trial outcomes.

Abstract

Clinical trials often seek to determine the superiority, equivalence, or non-inferiority of an experimental condition (e.g., a new drug) compared to a control condition (e.g., a placebo or an already existing drug). The use of frequentist statistical methods to analyze data for these types of designs is ubiquitous even though they have several limitations. Bayesian inference remedies many of these shortcomings and allows for intuitive interpretations. In this article, we outline the frequentist conceptualization of superiority, equivalence, and non-inferiority designs and discuss its disadvantages. Subsequently, we explain how Bayes factors can be used to compare the relative plausibility of competing hypotheses. We present baymedr, an R package and web application, that provides user-friendly tools for the computation of Bayes factors for superiority, equivalence, and non-inferiority designs. Instructions on how to use baymedr are provided and an example illustrates how already existing results can be reanalyzed with baymedr.