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Abstract:
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The modified Box-Meyer method (MBMM) has been proposed to identify active factors in an unreplicated screening experiment. This work aims to introduce the MBMM into the analysis of a screening experiment with lifetime data. Both experiments with and without replicates are considered. Unlike the original MBMM, we propose a quasi-empirical Bayes approach to estimate the hyper-parameters. By doing so, the computational complexity is reduced. We illustrate the proposed approach by analyzing two examples, and all the active factors are identified successfully in both examples.
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