Nonparametric Methods for Detecting Treatment Effects in Repeated-Measures Designs
重复测量设计中检测处理效应的非参数方法
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…