Weighted rank statistics in factorial designs with fixed effects
Weighted rank statistics in factorial designs with fixed effects
复制标题
具有固定效应的因子设计中的加权排名统计
DOI：
10.1111/1467-9574.00192
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发表时间：
2002
影响因子：
1.5
通讯作者：
M. Puri
中科院分区：
文献类型：
--
作者：
E. Brunner;S. Domhof;M. Puri
考虑了两个固定因子析因设计分析的非参数方法。样本量可能不相等，并且分布函数不假定为连续的。通过排序程序检验主效应和交互作用的非参数假设，其中根据一个因子水平内的不同样本量对统计量进行加权。模拟表明，如果所有治疗组合的单元内样本量至少为7，则极限正态分布以及t-和F-分布的近似值非常准确。此外，事实证明，加权统计量的功效比未加权统计量的功效高得多。所建议的程序的应用证明了从一个临床试验的数据集与有序的分类数据的分析。
Nonparametric methods for the analysis of factorial designs with two fixed factors are considered. The sample sizes may be unequal and the distribution functions are not assumed to be continuous. Nonparametric hypotheses for the main effects and for the interaction are tested by ranking procedures where the statistics are weighted according to the different sample sizes within the levels of one factor. Simulations show that the approximations by the limiting normal distribution and by the t‐ and F‐distributions are quite accurate if the samples sizes within the cells are at least 7 for all treatment combinations. Moreover, it turns out that the power for the weighted statistics is much higher than for the unweighted statistics. The application of the suggested procedures is demonstrated by the analysis of a data set from a clinical trial with ordered categorical data.