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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98645


    Title: Comparing several population means: a parametric bootstrap method, and its comparison with usual ANOVA F test as well as ANOM
    Authors: Chang, Ching-Hui;Pal, Nabendu;Wooi, Khai Lim;Lin, Jyh-Jiuan
    Contributors: 淡江大學統計學系
    Keywords: Comparing means;Hypothesis testing;Power function;Size;Primary 62F03;62F25;Secondary 62E17
    Date: 2010-03
    Issue Date: 2014-09-03 17:35:36 (UTC+8)
    Publisher: Springer-Verlag
    Abstract: This paper deals with testing the equality of several homoscedastic normal population means. We introduce a newly developed computational approach test (CAT), which is essentially a parametric bootstrap method, and discuss its merits and demerits. In the process of studying the CAT’s usefulness, we compare it with the traditional one-way ANOVA’s F test as well as the analysis of means (ANOM) method. Further, the model robustness of the above three methods have been studied under the ‘t-model’. The motivation behind the proposed CAT is to provide the applied researchers a statistical tool to carry out a comparison of several population means, in a parametric setup, without worrying about the sampling distribution of the inherent test statistic. The CAT can be used to test the equality of several means when the populations are assumed to be heteroscedastic t-distributions.
    Relation: Computational Statistics 25(1), pp.71-95
    DOI: 10.1007/s00180-009-0162-z
    Appears in Collections:[統計學系暨研究所] 期刊論文

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