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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41654


    Title: Extended rank analysis of covariance as a more efficient matched analysis considering trend information
    Authors: 陳主智;Chen, Chu-chih
    Contributors: 淡江大學數學學系
    Keywords: Asymptotic relative efficiency;Caliper matching;Category matching;Concomitant;Mantel-Haenszel statistic;Tolerance
    Date: 2001-11-12
    Issue Date: 2010-01-28
    Publisher: Wiley-Blackwell
    Abstract: Classical matched analysis, regarded as analysis of covariance (ANOCOVA) in a broad sense, makes no attempt in modeling and may therefore be inefficient. In this paper, we discuss the relative efficiencies of the ERMP (extended rank and matched-pair) test (Chen and Quade, 2000) to standard matched methods, and extend it to the case of multivariate covariables X. Taking advantage of trend information between the response Y and the covariables X by ranking after matching, ERMP test achieves better efficiency than a proposed class of weighted matched statistics. When Y is dichotomous, the optimal weighted matched statistic is equivalent to the Mantel-Haenszel statistic. Example and simulation results also suggest the conclusion.
    Relation: Biometrical Journal 43(7), pp.895-907
    DOI: 10.1002/1521-4036(200111)43:7<895::AID-BIMJ895>3.0.CO;2-8
    Appears in Collections:[數學學系暨研究所] 期刊論文

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