Multivariate Mann–Whitney Estimators for the Comparison of Two Treatments in a Three-Period Crossover Study with Randomly Missing Data
Multivariate Mann–Whitney Estimators for the Comparison of Two Treatments in a Three-Period Crossover Study with Randomly Missing Data
复制标题
用于比较具有随机缺失数据的三期交叉研究中两种治疗方法的多元曼-惠特尼估计量
DOI：
10.1080/10543401003618108
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发表时间：
2010
影响因子：
1.1
通讯作者：
G. Koch
中科院分区：
文献类型：
--
作者：
Atsushi Kawaguchi;G. Koch
本文讨论了多元Mann-Whitney估计在四个序列组三个周期的交叉研究中对严格有序响应变量的两种处理的比较。还考虑了管理随机丢失数据的方法和基准期内不同组之间无差异的非参数协方差调整。与Mann-Whitney估计量的线性Logistic模型中的处理比较有关的估计量通过降维和加权最小二乘的Bradley-Terry模型来确定。这些估计值可以作为统计检验和可信区间的基础。文中给出了算例计算结果。仿真研究表明，这两种方法对第一类误差和功率都有合理的控制。
This paper discusses the application of multivariate Mann–Whitney estimators to the comparison of two treatments for a strictly ordinal response variable in a crossover study with four sequence groups and three periods. Ways of managing randomly missing data and nonparametric covariance adjustment for no differences among groups for a baseline period have consideration as well. Estimators pertaining to treatment comparisons in linear logistic models for the Mann–Whitney estimators have determination through a Bradley–Terry model for dimension reduction and weighted least squares. These estimators can be the basis for both statistical tests and confidence intervals. The methods in this paper have their results presented for an example. Simulation studies for the methods show that they have reasonable control of type 1 error and power.