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平衡不完全重复测量设计中的秩变换方法AI 解读

Asymptotic properties of statistics designed to detect general alternatives in compound symmetric balanced incomplete repeated-measures designs with fixed treatment effects are investigated. Included in this study are the analysis of variance (ANOVA) F statistic, its rank transform Durbin's statistic. By making asymptotic relative efficiency comparisions among these statistics when they have been computed with and without mean alignment, valuable new insight into their…

重复测量设计中检测处理效应的非参数方法AI 解读

Sufficient conditions are given that guarantee the limiting distribution of a test proposed by Agresti and Pendergast (1986) to detect treatment effects in repeated-measures designs. The test, which is appropriate for either the original or aligned data, is related to one proposed by Koch (1969) and to the rank-transformation statistic. Using Pitman asymptotic-relative-efficiency comparisons, situations are presented where these tests are more efficient than their standard…

随机完全区组设计中有序备择的分布无关秩检验AI 解读

A distribution-free rank test for detecting ordered alternatives in randomized complete block designs and repeated measures designs is proposed for four or fewer treatments. The null hypothesis distribution of the statistic is well-known and readily available to the user. The article establishes the asymptotic normality of an appropriately standardized form of the statistic and the consistency of the test. Asymptotic relative efficiency comparisons are made with Jonckheere's…

检测二元总体的边际尺度差异AI 解读

A conditional test is proposed that uses the null hypothesis of bivariate symmetry to detect unequal marginal scales in a bivariate population. The asymptotic normality of the test statistic and the consistency of the test are established. Asymptotic relative efficiency comparisons are made with the standard parametric test in both the bivariate normal case and in a trivariate reduction model case and with two of Sen's (1967) tests in the bivariate normal case. The good…