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Perspectives on Bayesian inference and their implications for data analysis.
1Department of Psychology, Arizona State University.
Psychological Methods
|December 23, 2021
Summary
Bayesian methods are increasingly popular in research. This paper highlights five distinct perspectives on applying Bayesian methods, showing how different viewpoints impact modeling and reporting practices.
Area of Science:
- Statistics
- Computational Statistics
Background:
- Bayesian methods usage has grown due to technological advancements.
- This has led to increased recommendations and best practices for Bayesian data analysis.
Purpose of the Study:
- To describe five distinct perspectives for applying Bayesian methods.
- To illustrate how these perspectives influence modeling and reporting.
- To emphasize the heterogeneity of defensible Bayesian practices.
Main Methods:
- Literature review and conceptual analysis.
- Identification and description of five Bayesian application perspectives.
- Discussion of methodological examples within each perspective.
Main Results:
- Five distinct perspectives on Bayesian methods are presented.
- Different perspectives lead to varied modeling and reporting recommendations.
- Practices reasonable under one perspective may be unreasonable under another.
Conclusions:
- There is significant diversity in defensible Bayesian practices.
- Understanding these diverse perspectives fosters appreciation for varied orientations in Bayesian analysis.
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