有哪些信誉好的足球投注网站multiple category-lot quality assurance sampling a new classification system with application to schistosomiasis control多个category-lot质量保证抽样的新分类系统与应用程序控制血吸虫病.pdfVIP
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multiple category-lot quality assurance sampling a new classification system with application to schistosomiasis control多个category-lot质量保证抽样的新分类系统与应用程序控制血吸虫病
Multiple Category-Lot Quality Assurance Sampling: A New Classification System with Application to Schistosomiasis Control 1,2 3 4,5 2 Casey Olives , Joseph J. Valadez *, Simon J. Brooker , Marcello Pagano 1 Department of Biostatistics, University of Washington, Seattle, Washington, United States of America, 2 Department of Biostatistics, Harvard University, Boston, Massachusetts, United States of America, 3 Department of International Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom, 4 Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom, 5 Kenya Medical Research Institute-Wellcome Trust Research Programme, Nairobi, Kenya Abstract Background: Originally a binary classifier, Lot Quality Assurance Sampling (LQAS) has proven to be a useful tool for classification of the prevalence of Schistosoma mansoni into multiple categories (#10%, .10 and ,50%, $50%), and semi- curtailed sampling has been shown to effectively reduce the number of observations needed to reach a decision. To date the statistical underpinnings for Multiple Category-LQAS (MC-LQAS) have not received full treatment. We explore the analytical properties of MC-LQAS, and validate its use for the classification of S. mansoni prevalence in multiple settings in East Africa. Methodology: We outline MC-LQAS design principles and formulae for operating characteristic curves. In addition, we derive the average sample number for MC-LQAS when utilizing semi-curtailed sampling and introduce curtailed sampling in this setting. We also assess the performance of MC-LQAS designs with maximum sample sizes of n = 15 and n = 25 via a weigh
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