We consider a two-group randomized clinical trial, where mortality affects the assessment of a follow-up continuous outcome. Using the worst-rank composite endpoint, we develop a weighted Wilcoxon-Mann-Whitney test statistic to analyze the data. We determine the optimal weights for the Wilcoxon-Mann-Whitney test statistic that maximize its power. We derive a formula for its power and demonstrat...

The Wilcoxon signed rank test is a frequently used nonparametric test for paired data (e.g., consisting of pre- and posttreatment measurements) based on independent units of analysis. This test cannot be used for paired comparisons arising from clustered data (e.g., if paired comparisons are available for each of two eyes of an individual). To incorporate clustering, a generalization of the ran...

In many research disciplines, hypothesis tests are applied to evaluate whether findings are statistically significant or could be explained by chance. The Wilcoxon-Mann-Whitney (WMW) test is among the most popular hypothesis tests in medicine and life science to analyze if two groups of samples are equally distributed. This nonparametric statistical homogeneity test is commonly applied in molec...

Gene set analysis is widely used to facilitate biological interpretations in the analyses of differential expression from high throughput profiling data. Wilcoxon Rank-Sum (WRS) test is one of the commonly used methods in gene set enrichment analysis. It compares the ranks of genes in a gene set against those of genes outside the gene set. This method is easy to implement and it eliminates the ...

Bayesian methods are ubiquitous in machine learning. Nevertheless, the analysis of empirical results is typically performed by frequentist tests. This implies dealing with null hypothesis significance tests and p-values, even though the shortcomings of such methods are well known. We propose a nonparametric Bayesian version of the Wilcoxon signed-rank test using a Dirichlet process (DP) based p...

The selection of an adequate regression model is the basis for obtaining accurate and reproducible results during the bionalytical method validation. Given the wide concentration range, frequently present in bioanalytical assays, heteroscedasticity of the data may be expected. Several weighted linear and quadratic regression models were evaluated during the selection of the adequate curve fit u...

Non-parametric paired analyses are approached through the same logic as the parametric paired t-tests: a 2 sample paired analysis can be reduced to a 1 sample test by creating a single distribution of the differences between each pair. If the distribution of the differences are nonnormal, and cannot be normalized by transforming the data to some other ratio scale, a 1 sample non-parametric test...

UnifyPow is a freeware SAS ® macro that performs statistical power analysis and other matters related to sample-size choice. Its functionality covers an extensive set of methods. One-group tests include the t and Wilcoxon for H 0 : μ = μ 0 ; the binomial and Z approximation for H 0 : π = π 0 ; t and Wilcoxon for paired means; McNemar's for paired proportions; and Fishers's r-to-Z for H 0 : ρ = ...

INTRODUCTION Among patients with acute myeloid leukemia (AML), the DACO-016 randomized study showed reduction in mortality for decitabine [Dacogen(®) (DAC), Eisai Inc., Woodcliff Lake, NJ, USA] compared with treatment choice (TC): at primary analysis the hazard ratio (HR) was 0.85 (95% confidence interval 0.69-1.04; stratified log-rank P = 0.108). With two interim analyses, two-sided alpha was ...

In psychological research sometimes non-parametric procedures are in use in cases, where the corresponding parametric procedure is preferable. This is mainly due to the fact that we pay too much attention to the possible violation of the normality assumption which is needed to derive the exact distribution of the statistic used in the parametric approach. An example is the t-test and its non-pa...