Efficient Augmented Block Designs for Unreplicated Test Treatments Along with Replicated Controls

Rahul Mukerjee
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Abstract

Augmented block designs for unreplicated test treatments are investigated under the A- and MV-criteria with respect to test versus test, control versus test and control versus control comparisons. We derive design-independent lower bounds on these criteria over a wide class of competing designs. These bounds are useful benchmarks and the resulting expressions for efficiencies enable objective assessment of any given design under theA- and MV-criteria. It is seen that the use of BIB designs and duals thereof as well as existing block design catalogs often leads to very high efficiencies for all three types of comparisons. Illustrative examples, including a large-scale one, are presented.

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无重复试验处理和重复对照的高效扩增区组设计
根据 A 标准和 MV 标准,研究了试验与试验、对照与试验、对照与对照比较中的无重复试验处理的扩充区组设计。我们推导出了这些标准在众多竞争设计中的独立于设计的下限。这些下限是有用的基准,由此得出的效率表达式可根据 A 标准和 MV 标准对任何给定设计进行客观评估。我们可以看到,使用 BIB 设计及其对偶以及现有的块设计目录,往往能为所有三种类型的比较带来非常高的效率。文中还介绍了一些示例,包括一个大型示例。
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来源期刊
CiteScore
2.70
自引率
7.10%
发文量
38
审稿时长
>12 weeks
期刊介绍: The Journal of Agricultural, Biological and Environmental Statistics (JABES) publishes papers that introduce new statistical methods to solve practical problems in the agricultural sciences, the biological sciences (including biotechnology), and the environmental sciences (including those dealing with natural resources). Papers that apply existing methods in a novel context are also encouraged. Interdisciplinary papers and papers that illustrate the application of new and important statistical methods using real data are strongly encouraged. The journal does not normally publish papers that have a primary focus on human genetics, human health, or medical statistics.
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