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- W3100731490 abstract "Abstract When developing a product, it is important to consider product performance from a user perspective. This type of evaluation can be done through operational testing—assessing the ability of representative users to satisfactorily accomplish tasks with the product in operationally representative environments. This process can be expensive and time‐consuming, but is critical to understanding whether the product can adequately do the job for which it was designed. We show how an existing design of experiments (DOEs) process for operational testing can be leveraged to construct a Bayesian adaptive design. This design, nested within the larger design created by the DOE process, allows interim analyses to stop testing early for success or futility. Representative simulations are presented to demonstrate how these interim analyses can be used in an operational test setting, and reductions in necessary test events are shown. The application of Bayesian‐adaptive design methods will allow future operational testing to be conducted in less time and at less expense, on average, without compromising the ability of the existing process to verify the product meets the user's needs." @default.
- W3100731490 created "2020-11-23" @default.
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- W3100731490 date "2020-11-17" @default.
- W3100731490 modified "2023-10-18" @default.
- W3100731490 title "A framework for improving the efficiency of operational testing through Bayesian adaptive design" @default.
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- W3100731490 doi "https://doi.org/10.1002/qre.2802" @default.
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