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dc.contributor.authorSevern, Daniel Ernest
dc.contributor.authorSteiner, Stefan H.
dc.contributor.authorMacKay, R. Jock 19:32:43 (GMT) 19:32:43 (GMT)
dc.descriptionThe final publication is available at Elsevier via © 2019. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
dc.description.abstractWe investigate efficient plans to assess the misclassification error rates of a binary measurement system used as an in-line inspection protocol. We assume that parts can be inspected repeatedly and that each part has its own (latent) misclassification rate. We propose a three-phase assessment plan. Phase I consists of data from recent inspection history. In Phase II, we select a sample of failed parts that we re-measure multiple times with the binary measurement system of interest. In Phase III, we verify a carefully selected subsample of the parts from Phase II with the aid of a binary gold standard measurement system. We show that the proposed plan is a substantial improvement over existing assessment plans in terms of cost and/or precision.en
dc.description.sponsorshipThis research was supported in part by the Natural Sciences and Engineering Research Council (NSERC) discovery grant #105240.en
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.subjectbaseline dataen
dc.subjectbinary measurement system assessmenten
dc.subjectconditional samplingen
dc.subjecttargeted verificationen
dc.titleAssessing a binary measurement system: A new plan using targeted verification with conditional sampling and baseline informationen
dcterms.bibliographicCitationD.E. Severn, S.H. Steiner, R.J. MacKay, Assessing a Binary Measurement System: A New Plan Using Targeted Verification with Conditional Sampling and Baseline Information, Measurement (2019), doi:
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2Statistics and Actuarial Scienceen

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