New Procedure in Testing Differences between Two Groups
TL;DR: In this paper, the pseudo-median was proposed as the location measure of interest for the one-sample nonparametric Wilcoxon procedure in a two-group setting.
read more
Abstract: Despite the theoretical correctness of the t-test in testing differences between two groups and the existence of the nonparametric backup, i.e. Mann-Whitney-Wilcoxon test, these test fail to simultaneously control Type I error and maintain adequate power under certain condition. This study intends to alleviate this problem by a pplying the pseudo-median as the location measure of interest into the one-sample nonparametric Wilcoxon procedure in a two group setting. Pseudo-median is the median of all possible differences of observations from the two groups. Since the sampling distribution of this procedure is intractable, the bootstrap method was used to achieve the significance level. The finding shows that the new p rocedure has the ability to control Type I error rates and maintaining high power rates regardless of distributional shape whether symmetrical or asymmetrical. The performance of the new procedure is compatible to t-test and Mann-Whitney-Wilcoxon test.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
References
A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong
Andrais Vargha,Harold D. Delaney +1 more
TL;DR: McGraw and Wong as mentioned in this paper described an appealing index of effect size, called CL, which measures the difference between two populations in terms of the probability that a score sampled at random from...
1.3K
Statistical power analysis
Kevin R. Murphy,Brett Myors +1 more
- 11 Dec 2013
TL;DR: Statistical power analysis, Statistical power analysis as mentioned in this paper, statistical power analysis, کتابخانه دیجیتال جندی شاپور اهواز
1.2K
•Book
Statistical Power Analysis: A Simple and General Model for Traditional and Modern Hypothesis Tests
Kevin R. Murphy,Brett Myors +1 more
- 01 Apr 1998
TL;DR: In this paper, the authors present a simple and general model for power analysis for minimum-effect tests, using power analysis with t-Tests and the analysis of variance, and the Implications of power analysis.
930
A common language effect size statistic.
Kenneth O. McGraw,S. P. Wong +1 more
TL;DR: The Common Language Effect Size Indicator (CLEI) as mentioned in this paper measures the likelihood that a score sampled from one distribution will be greater than a score from another distribution, and can be used for expressing the effect observed in both independent and related sample designs and in both 2-group and n-group designs.
882