A Framework for Using Priors in a Continuum of Testing

Document Type

Article

Publication Date

2024

Abstract

A strength of the Bayesian paradigm is that it can leverage all available information, to include subject matter expert (SME) opinion and previous (possibly dissimilar) data, through prior probabilities (priors). This article develops a framework for thinking about how differently characterized priors can be appropriately used throughout the continuum of testing. In addition to the application of various priors, the application of the evolution of the priors also contributes greatly to analytical understanding and will be addressed, considering cases such as when a system's state significantly changes (e.g., is modified) during phases of testing. The evolution of priors can start with priors attempting to provide no information and evolve toward priors that capture the (newly) available information. This article further discusses priors based on institutional knowledge, as well as those based on previous testing data; the focus will be on previous, in some ways dissimilar, data, relative to a current test event. A discussion on which priors might be more common in various phases of testing, types of information that can be used in priors, and how priors evolve as information accumulates is also included. Finally, a real-world example using the Stryker family of vehicles demonstrates how priors can be employed in a continuum-of-testing construct.

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Source Publication

Military Operations Research (ISSN 1082-5983 | e-ISSN 2163-2758)

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