baymedr

baymedr computes Bayes factors to evaluate superiority, equivalence, and non-inferiority hypotheses in clinical trial data.

Key Features:

• Computation of Bayes factors: Calculates Bayes factors to quantify evidence for competing hypotheses in clinical trials.
• Bayesian inference: Uses Bayesian inference to assess the relative plausibility of competing hypotheses.
• Support for trial designs: Supports superiority, equivalence, and non-inferiority clinical trial designs, including comparisons between experimental conditions (e.g., new drug) and control conditions (e.g., placebo or existing treatment).
• Data input flexibility: Accepts raw data or summary statistics as inputs for analysis.
• Reanalysis capability: Enables reanalysis of existing trial results using Bayesian methods and Bayes factors.

Scientific Applications:

• Superiority testing: Quantifies evidence that an experimental treatment is superior to a control.
• Equivalence testing: Evaluates evidence for equivalence between treatments.
• Non-inferiority testing: Assesses evidence that an experimental treatment is not inferior to a control.
• Reanalysis of published trials: Reinterprets existing frequentist trial results using Bayesian evidence measures.

Methodology:

Implements Bayesian inference via calculation of Bayes factors to compare the relative plausibility of competing hypotheses and operates on either raw data or summary statistics.