Project description:For the two-sample problem, the Wilcoxon-Mann-Whitney (WMW) test is used frequently: it is simple to explain (a permutation test on the difference in mean ranks), it handles continuous or ordinal responses, it can be implemented for large or small samples, it is robust to outliers, it requires few assumptions, and it is efficient in many cases. Unfortunately, the WMW test is rarely presented with an effect estimate and confidence interval. A natural effect parameter associated with this test is the Mann-Whitney parameter, φ = Pr[ X<Y ] + 0.5 Pr[X = Y ]. Ideally, we desire confidence intervals on φ that are compatible with the WMW test, meaning the test rejects at level α if and only if the 100(1 - α)% confidence interval on the Mann-Whitney parameter excludes 1/2. Existing confidence interval procedures on φ are not compatible with the usual asymptotic implementation of the WMW test that uses a continuity correction nor are they compatible with exact WMW tests. We develop compatible confidence interval procedures for the asymptotic WMW tests and confidence interval procedures for some exact WMW tests that appear to be compatible. We discuss assumptions and interpretation of the resulting tests and confidence intervals. We provide the wmwTest function of the asht R package to calculate all of the developed confidence intervals.
Project description:The goal of the experiment was to identify genes downstream of the SHOX2 transcription factor during mouse forelimb development. Triplicate Samples were isolated from Shox2 mutants and wildtype/heterozygote limbs at E10.5 and E11.5.
Project description:We propose an extension of the Wilcoxon-Mann-Whitney test to compare two groups when the outcome variable is latent. We empirically demonstrate that the test can have superior power properties relative to tests based on Structural Equation Modeling for a variety of settings. In addition, several other advantages of the Wilcoxon-Mann-Whitney test are retained such as robustness to outliers and good small sample performance. We demonstrate the proposed methodology on a case study.
Project description:Late phase clinical trials are occasionally planned with one or more interim analyses to allow for early termination or adaptation of the study. While extensive theory has been developed for the analysis of ordered categorical data in terms of the Wilcoxon-Mann-Whitney test, there has been comparatively little discussion in the group sequential literature on how to provide repeated confidence intervals and simple power formulas to ease sample size determination. Dealing more broadly with the nonparametric Behrens-Fisher problem, we focus on the comparison of two parallel treatment arms and show that the Wilcoxon-Mann-Whitney test, the Brunner-Munzel test, as well as a test procedure based on the log win odds, a modification of the win ratio, asymptotically follow the canonical joint distribution. In addition to developing power formulas based on these results, simulations confirm the adequacy of the proposed methods for a range of scenarios. Lastly, we apply our methodology to the FREEDOMS clinical trial (ClinicalTrials.gov Identifier: NCT00289978) in patients with relapse-remitting multiple sclerosis.