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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

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Published on: March 1, 2022

Bayesian inference in two-arm trials using relative belief ratios.

Saman Muthukumarana¹, Michael Evans²

¹Department of Statistics, University of Manitoba, Manitoba R3T 2N2, Winnipeg, Canada.

Pharmaceutical Statistics

|August 16, 2015

Summary

This study introduces a Bayesian approach to address inference challenges in two-arm trials. It offers a clear measure of statistical evidence, mitigating subjectivity concerns through prior model checking.

Keywords:

bias induced from a prior checking for prior-data conflict equivalence measuring statistical evidence model checking noninferiority relative belief ratios

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Area of Science:

Biostatistics
Clinical Trial Methodology
Statistical Inference

Background:

Existing inference methodologies for two-arm trials face documented difficulties.
Bayesian methods are often perceived as subjective, posing challenges in clinical research.
Need for robust statistical evidence measures in trial analysis.

Purpose of the Study:

To propose an alternative Bayesian approach for inference problems in two-arm trials.
To provide an explicit measure of statistical evidence and its strength.
To address concerns regarding subjectivity in Bayesian methodologies.

Main Methods:

Development of a Bayesian framework for two-arm trial inference.
Incorporation of prior model checking to assess bias.
Implementation of prior-data conflict checks.

Main Results:

The proposed Bayesian approach effectively addresses existing inference difficulties.
Provides a quantifiable measure of statistical evidence and its strength.
Demonstrates methods to mitigate concerns about prior subjectivity.

Conclusions:

The alternative Bayesian approach offers a robust solution for two-arm trial inference.
Explicit evidence measures enhance interpretability and reduce subjectivity.
Prior checking strategies ensure the reliability of Bayesian analyses in clinical trials.