Wilcoxon Rank-Based Tests for Clustered Data with R Package clusrank

Rank-Sum Tests for Clustered Data

The Wilcoxon rank-sum test is widely used to test the equality of two populations, because it makes fewer distributional assumptions than parametric procedures such as the t-test. However, the Wilcoxon rank-sum test can be used only if data are independent. When data are clustered, tests based on generalized estimating equations (GEEs) that generalize the t-test have been proposed. Here we deve...

The Wilcoxon signed rank test for paired comparisons of clustered data.

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...

Weighted Wilcoxon-Type Rank Test for Interval Censored Data

Interval censored (IC) failure time data are often observed in medical follow-up studies and clinical trials where subjects can only be followed periodically, and the failure time can only be known to lie in an interval. In this paper, we propose a weightedWilcoxontype rank test for the problem of comparing two IC samples. Under a very general sampling technique developed by Fay (1999), the mea...

R-package FME : MCMC tests

This vignette tests the Markov chain Monte Carlo (MCMC) implementation of Rpackage FME (Soetaert and Petzoldt 2010). It includes the delayed rejection and adaptive Metropolis algorithm (Haario, Laine, Mira, and Saksman 2006)

Generalizing the Wilcoxon rank-sum test for interval data