Tests for High-Dimensional Regression Coefficients With Factorial Designs
Tests for High-Dimensional Regression Coefficients With Factorial Designs
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DOI：
10.1198/jasa.2011.tm10284
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发表时间：
2011-03-01
影响因子：
3.7
通讯作者：
Chen, Song Xi
中科院分区：
文献类型：
--
作者：
Zhong, Ping-Shou;Chen, Song Xi
本文提出了一种同时检验高维线性回归模型系数的方法。建议的测试是专为“大p，小n”的情况下，传统的F检验不再适用。我们推导出高维零假设和各种情况下的替代品，允许电源评估的建议的检验统计量的渐近分布。我们还评估了中等维度模型的F检验的能力。在考虑了实验设计后，利用所提出的检验方法对约克郡后备母猪的微阵列数据进行分析，以发现与甲状腺激素显著相关的显著基因本体论术语。
We propose simultaneous tests for coefficients in high-dimensional linear regression models with factorial designs. The proposed tests are designed for the "large p, small n" situations where the conventional F-test is no longer applicable. We derive the asymptotic distribution of the proposed test statistic under the high-dimensional null hypothesis and various scenarios of the alternatives, which allow power evaluations. We also evaluate the power of the F-test for models of moderate dimension. The proposed tests are employed to analyze a microarray data on Yorkshire Gilts to find significant gene ontology terms which are significantly associated with the thyroid hormone after accounting for the designs of the experiment.