Work

A General Framework for the Multiple Nonparametric Behrens–Fisher Problem With Dependent Replicates

Year: 2024

Type: article

Abstract: ABSTRACT In many trials and experiments, subjects are not only observed once but multiple times, resulting in a cluster of possibly correlated observations (e.g., brain regions per patient). Observations often do not fulfill model assumptions of mixed models and require the use of nonparametric methods. In this article, we develop and present a purely nonparametric rank‐based procedure that flexibly allows the unbiased and consistent estimation of the Wilcoxon–Mann–Whitney effect in clustered data designs. Compared with existing methods, we allow flexible weights to be used in effect estimation. Additionally, we develop global and multiple contrast test procedures to test null hypotheses formulated regarding the generalized Mann–Whitney effects and for the computation of range‐preserving simultaneous confidence intervals in a unified way. Extensive simulation studies show that these methods control the type‐I error rate well and have reasonable power to detect alternatives in various situations.

Source: Statistics in Medicine

DOI: 10.1002/sim.10262

Authors: Erin Sprünken, Robert Mertens, Frank Konietschke

Institution: Charité - Universitätsmedizin Berlin

Language: English

Topic: Statistical Methods in Clinical Trials

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $5,190

Funder: Deutsche Forschungsgemeinschaft