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The Role of Expert Judgment in Statistical Inference and Evidence-Based Decision-Making.
Naomi C Brownstein1,2,3, Thomas A Louis4, Anthony O'Hagan5
1Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL.
The American Statistician
|May 7, 2019
Summary
Expert judgment is crucial for statistical inference, guiding decisions in research and clinical trials. Statisticians must proactively engage in all study phases for robust scientific conclusions.
Area of Science:
- Statistics
- Scientific Inference
- Decision Making
Background:
- Expert opinion plays a role in statistical inference.
- The 2017 ASA Symposium on Statistical Inference discussed expert judgment.
- Bayesian and frequentist perspectives on expert input were considered.
Purpose of the Study:
- To present a unified statement on the role of expert judgment in statistics.
- To outline processes for incorporating expert input from both Bayesian and frequentist viewpoints.
- To illustrate the application of expert judgment in case studies.
Main Methods:
- Review of expert opinion roles in scientific inference.
- Analysis of subjectivity in the inference and decision-making cycle.
- Case studies involving a clinical trial and greenhouse gas emissions.
Main Results:
- Expert judgment is integral to statistical inference and decision-making.
- Objective information and uncertainty assessment are vital for sound expert judgment.
- Case studies demonstrate the practical application and importance of expert input.
Conclusions:
- Expert judgment, when based on objective information, enhances statistical inference.
- Statisticians should be more proactive in all stages of research, from design to communication.
- A unified approach to incorporating expert judgment benefits scientific rigor.
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