The Wilcoxon Signed Rank Test for Paired Comparisons of Clustered Data

DOI10.1111/j.1541-0420.2005.00389.xzbMath1091.62036OpenAlexW1982980578WikidataQ31034489 ScholiaQ31034489MaRDI QIDQ5473222

Bernard Rosner, Robert J. Glynn, Mei-Ling Ting Lee

Publication date: 20 June 2006

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2005.00389.x

zbMATH Keywords

clustered datapaired dataophthalmologic data

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Paired and multiple comparisons; multiple testing (62J15)

Related Items (16)

Quantile inference based on clustered data ⋮ Permutation tests under a rotating sampling plan with clustered data ⋮ Improving the Wilcoxon signed rank test by a kernel smooth probability integral transformation ⋮ The nonparametric Behrens–Fisher problem in partially complete clustered data ⋮ Rank tests in unmatched clustered randomized trials applied to a study of teacher training ⋮ Unnamed Item ⋮ Two sample tests for the nonparametric Behrens–Fisher problem with clustered data ⋮ A Signed-Rank Test for Clustered Data ⋮ A weighted multivariate signed-rank test for cluster-correlated data ⋮ Weighted Wilcoxon‐Type Smoothly Clipped Absolute Deviation Method ⋮ One-sample location test based on the sign and Wilcoxon signed-rank tests ⋮ One-sample location tests for multilevel data ⋮ Composite empirical likelihood for multisample clustered data ⋮ Optimised one-class classification performance ⋮ A general class of signed-rank tests for clustered data when the cluster size is potentially informative ⋮ Weighted rank tests and Hodges–Lehmann estimates for the multivariate two-sample location problem with clustered data

Cites Work

• Longitudinal data analysis using generalized linear models
• Incorporation of Clustering Effects for the Wilcoxon Rank Sum Test: A Large‐Sample Approach
• A Review of Inference Procedures for the Intraclass Correlation Coefficient in the One-Way Random Effects Model
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