A Signed-Rank Test for Clustered Data

DOI10.1111/j.1541-0420.2007.00923.xzbMath1137.62024OpenAlexW1972769562WikidataQ31134815 ScholiaQ31134815MaRDI QIDQ108321

Glen A. Satten, Somnath Datta, Glen A. Satten

Publication date: June 2008

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2007.00923.x

zbMATH Keywords

repeated measuressimulationsdependent datapaired comparisons

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)

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Cites Work

• Unnamed Item
• Marginal Analyses of Clustered Data When Cluster Size Is Informative
• An enhanced sign test for dependent binary data with small numbers of clusters
• Within-cluster resampling
• Modeling Longitudinal Data with Ordinal Response by Varying Coefficients
• An affine‐invariant multivariate sign test for cluster correlated data
• A weighted multivariate sign test for cluster-correlated data
• The Wilcoxon Signed Rank Test for Paired Comparisons of Clustered Data
• Rank-Sum Tests for Clustered Data