Extended rank analysis of covariance as a more efficient matched analysis considering trend information

機構典藏 > College of Sciences > Graduate Institute & Department of Mathematics > Journal Article > Item 987654321/41654

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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:	[Graduate Institute & Department of Mathematics] Journal Article

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