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非参数逐步多重比较程序AI 解读

Nonparametric multiple comparisons are discussed, with particular emphasis given to stepwise procedures. Nonparametric analogs of the stepwise all-subset procedure of Einot and Gabriel are presented, along with an ad hoc nonparametric analog of the Newman—Keuls procedure. These new procedures are compared among themselves and with nonstepwise procedures based on Type I error levels and comparisonwise power. It is shown that these stepwise nonparametric procedures control…

非参数逐步多重比较程序AI 解读

Nonparametric multiple comparisons are discussed, with particular emphasis given to stepwise procedures. Nonparametric analogs of the stepwise all-subset procedure of Einot and Gabriel are presented, along with an ad hoc nonparametric analog of the Newman—Keuls procedure. These new procedures are compared among themselves and with nonstepwise procedures based on Type I error levels and comparisonwise power. It is shown that these stepwise nonparametric procedures control…

双因素方差分析中主效应的 Friedman 型秩检验AI 解读

A distribution-free test is considered for testing main effects in a two-factor ANOVA. Large-sample properties (cell sizes tending to infinity) including efficiencies and the limiting distribution of the test statistic are obtained. For proportional frequencies a simple sum of squares formula is obtained for the test statistic and multiple comparison procedures are given. For general designs the statistic is expressed using generalized inverses. Some tables for the null…

随机区组设计中针对有序备择的无分布检验AI 解读

In this article we consider a class of test statistics that are useful for testing against ordered alternatives in balanced or unbalanced block designs. The approach consists of forming a statistic on each block and then combining the block statistics as a weighted sum to obtain one overall test statistic. Large-sample properties such as asymptotic normality and asymptotic relative efficiency as the number of blocks tends to infinity are considered. Throughout the article…