2015/08/31 by Rand R. Wilcox, Rand Wilcox, Wilcox, Rand
Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Methodology (stat.ME) #Multi-Criteria Decision Making #Statistical Methods and Inference #Statistical Methods in Clinical Trials #stat.ME
paper · pdf · doi:10.48550/arxiv.1509.00103
19 pages, 2 Figures
openalex publication_date 2015/08/31 · arxiv created 2015/09/01 · arxiv updated 2015/09/02 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
For two independent groups, let Mj(X) be some conditional measure of location for the jth group associated with some random variable Y given \mathbf X=(X1, X2). Let Ω=\X1, …, XK\ be a set of K points to be determined. An extant technique can be used to test H0: M1(X)=M2(X) for each X ∈ Ω without making any parametric assumption about Mj(X). But there are two general reasons to suspect that the method can have relatively low power. The paper reports simulation results on an alternative approach that is designed to test the global hypothesis H0: M1(X)=M2(X) for all X ∈ Ω. The main result is that the new method offers a distinct power advantage. Using data from the Well Elderly 2 study, it is illustrated that the alternative method can make a practical difference in terms of detecting a difference between two groups.