Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic on partly not identically distributed data

  • The established Hoeffding-Blum-Kiefer-Rosenblatt independence test statistic is investigated for partly not identically distributed data. Surprisingly, it turns out that the statistic has the well-known distribution-free limiting null distribution of the classical criterion under standard regularity conditions. An application is testing goodness-of-fit for the regression function in a non parametric random effects meta-regression model, where the consistency is obtained as well. Simulations investigate size and power of the approach for small and moderate sample sizes. A real data example based on clinical trials illustrates how the test can be used in applications.

Export metadata

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Daniel Gaigall
DOI:https://doi.org/10.1080/03610926.2020.1805767
ISSN:1532-415X
Parent Title (English):Communications in Statistics - Theory and Methods
Publisher:Taylor & Francis
Place of publication:London
Document Type:Article
Language:English
Year of Completion:2020
Date of first Publication:2020/08/14
Date of the Publication (Server):2023/01/16
Tag:Brownian Pillow; Hoeffding-Blum-Kiefer-Rosenblatt independence test; not identically distributed; random effects meta-regression model
Volume:51
Issue:12
First Page:4006
Last Page:4028
Link:https://doi.org/10.1080/03610926.2020.1805767
Zugriffsart:bezahl
Institutes:FH Aachen / Fachbereich Medizintechnik und Technomathematik
collections:Verlag / Taylor & Francis