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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/20618


    Title: A Simulation Study of Multiple Comparisons with the Average under Heteroscedasticity
    Authors: 吳淑妃;Wu, Shu-fei;Liao, B. X.
    Contributors: 淡江大學統計學系
    Keywords: Two-stage MCA, Single-stage MCA, Monte-Carlo simulation
    Date: 2004-01-01
    Issue Date: 2009-11-30 12:53:54 (UTC+8)
    Publisher: Taylor & Francis
    Abstract: In many experimental situations, the average treatment performance within its own group is used as a benchmark to be compared with each individual treatment. Multiple comparison procedures with the average (MCA) are thus proposed. A simulation comparison study of the traditional MCA, the single-stage MCA and the two-stage MCA for normal distribution under heteroscedasticity is investigated by the Monte-Carlo techniques in this paper. It was found that the two-stage MCA has shorter confidence length than the single-stage MCA for most cases and it is also more robust for non-normal distributions. Therefore, the two-stage MCA is recommended. But when the additional samples at the second stage could be costly, the data-analysis oriented single-stage MCA can be used. A biometrical example to illustrate the single-stage MCA and the two-stage MCA with equal confidence length is also given in this article.
    Relation: Communications in Statistics : Simulation and Computation 33(3), pp. 639-659
    DOI: 10.1081/SAC-200033355
    Appears in Collections:[統計學系暨研究所] 期刊論文

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