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    题名: Two-stage multiple comparisons with the average for normal distributions under heteroscedasticity
    其它题名: 雙階段的常態分配與平均的多重比較程序當變異數不等時
    作者: 吳淑妃;Wu, Shu-fei;Chen, Hubert J.
    贡献者: 淡江大學統計學系
    关键词: Two-stage procedure;Monte-Carlo techniques
    日期: 2000-04-28
    上传时间: 2009-11-30 12:54:56 (UTC+8)
    出版者: Elsevier
    摘要: In this article we propose a two-stage procedure for multiple comparisons with the average for normal distributions under heteroscedasity. One-sided and two-sided confidence intervals are proposed. These intervals can be used to identify a subset which includes all no-worse-than-the-average treatments in an experimental design and to identify better-than-the-average, worse-than-the-average and not-much-different-from-the-average products in agriculture, stock market, medical research, and auto models. An upper limit of critical values are obatined using Bonferroni inequality. But the approximate values are shown to be too conservative compared with the simulation critical values in Table 7. Therefore, simulation critical values should be used in our multiple comparison procedures. Statistical tables and software programs are provided for use in practice.
    關聯: Computational Statistics and Data Analysis 33(2), pp.201-213
    DOI: 10.1016/S0167-9473(99)00052-3
    显示于类别:[統計學系暨研究所] 期刊論文

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