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Bayesian statistical concepts with examples from rodent toxicology studies.

Gary J Larson1, Keith R Shockley2

  • 1Social & Scientific Systems, Inc., a DLH Holdings Corp Company, Durham, USA.

Laboratory Animals
|September 20, 2024
PubMed
Summary
This summary is machine-generated.

Bayesian statistics offer valuable tools for analyzing laboratory animal data, complementing traditional frequentist methods. Increased adoption of these accessible Bayesian approaches can enhance experimental science research.

Keywords:
Bayesian statisticshierarchical modelingprior distributionsrodent toxicologystatistical software

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Area of Science:

  • Statistics
  • Toxicology
  • Laboratory Animal Research

Background:

  • Statistics in experimental science typically relies on frequentist methods.
  • Bayesian statistical methods are less common in laboratory animal research and may be unfamiliar to practitioners.
  • Recent advancements have made Bayesian theory, methods, software, and education more accessible.

Purpose of the Study:

  • To provide an overview of Bayesian statistics.
  • To compare Bayesian and frequentist statistical methods.
  • To advocate for the adoption of Bayesian methods in laboratory animal research.

Main Methods:

  • A high-level overview of Bayesian statistical principles.
  • Comparison of Bayesian and frequentist approaches.
  • Illustrative examples from rodent toxicity research.

Main Results:

  • Bayesian methods offer significant advantages for analyzing laboratory animal data.
  • The accessibility of Bayesian tools has increased due to recent advancements.
  • Rodent toxicity research serves as a practical application case.

Conclusions:

  • Bayesian statistics present a valuable alternative and complement to frequentist methods in laboratory animal research.
  • Researchers are encouraged to increase their attention to and adoption of Bayesian methods.
  • The growing accessibility of Bayesian tools supports their wider implementation in experimental science.