在默认协方差结构下对混合模型进行推断的统计量的精确分布

Samaradasa Weerahandi, Ching-Ray Yu
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引用次数: 5

摘要

在从临床研究到商业分析等应用中大量使用混合模型的这个关键时刻,本文的目的是扩展Wald (Ann)的精确分布结果。数学。Stat. 18: 586-589, 1947)来处理涉及许多方差成分的模型。由于无法获得底层统计数据的精确分布结果,目前可用的方法仅为平衡ANOVA模型或简单回归模型提供小群体/样本推断。当有许多方差成分需要处理时,本文中开发的精确分布结果应该证明对通过参数自举法、基准法和广义p值法等方法进行推断是有用的。
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Exact distributions of statistics for making inferences on mixed models under the default covariance structure
At this juncture when mixed models are heavily employed in applications ranging from clinical research to business analytics, the purpose of this article is to extend the exact distributional result of Wald (Ann. Math. Stat. 18: 586–589, 1947) to handle models involving a number of variance components.Due to the unavailability of exact distributional results for underlying statistics, currently available methods provide small group/sample inference only for balanced ANOVA models or simple regression models. The exact distributional results developed in this article should prove useful in making inferences by such methods as parametric bootstrap, fiducial, and generalized p-value approach, when there are a number of variance components to deal with.
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来源期刊
Journal of Statistical Distributions and Applications
Journal of Statistical Distributions and Applications Decision Sciences-Statistics, Probability and Uncertainty
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审稿时长
13 weeks
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