Cited by 88Statistical Methods in Clinical TrialsStatistical Methods and Bayesian InferenceProbability and Statistical Research

Extension of the rank sum test for clustered data: Two-group comparisons with group membership defined at the subunit level

Rosner, Bernard, Glynn, Robert J., Lee, Mei‐Ling T.·2006·Biometrics

Abstract

Summary The Wilcoxon rank sum test is widely used for two‐group comparisons for nonnormal data. An assumption of this test is independence of sampling units both between and within groups. In ophthalmology, data are often collected on two eyes of an individual, which are highly correlated. In ophthalmological clinical trials, randomization is usually performed at the subject level, but the unit of analysis is the eye. If the eye is used as the unit of analysis, then a modification to the usual Wilcoxon rank sum variance formula must be made to account for the within‐cluster dependence. For some clustered data designs, where the unit of analysis is the subunit, group membership may be defined at the subunit level. For example, in some randomized ophthalmologic clinical trials, different treatments may be applied to fellow eyes of some patients, while the same treatment may be applied to fellow eyes of other patients. In general, binary eye‐specific covariates may be present (scored as exposed or unexposed) and one wishes to compare nonnormally distributed outcomes between exposed and unexposed eyes using the Wilcoxon rank sum test while accounting for the clustering. In this article, we present a corrected variance formula for the Wilcoxon rank sum statistic in the setting of eye (subunit)‐specific covariates. We apply it to compare ocular itching scores in ocular allergy patients between eyes treated with active versus placebo eye drops, where some patients receive the same eye drop in both eyes, while other patients receive different eye drops in fellow eyes. We also present comparisons between the clustered Wilcoxon test and each of the signed rank tests and mixed model approaches and show dramatic differences in power in favor of the clustered Wilcoxon test for some designs.

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Crossref · 10.1111/j.1541-0420.2006.00582.x

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  • The Rosner-Glynn-Lee variation of the Wilcoxon rank-sum test for clustered data was used to assess statistical significance between groups from data collected from multiple independent experiments performed at different times, treating each independent experiment as a cluster and accounting for variability both within and between independent experimental trials.

    “The Rosner–Glynn–Lee variation of the Wilcoxon rank-sum test for clustered data was applied to assess statistical significance between groups from data collected from multiple independent experiments performed at different times. This test treats data from each independent experiment as a “cluster” and accounts for variability both within and between independent experimental trials (Rosner et al.,”

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Authors
Rosner, B., Glynn, R. J., & Lee, M. T.
Affiliations
  • Harvard University (US)
  • The Ohio State University (US)
Corresponding author
Rosner, Bernard
Venue
Biometrics
Published
2006-06-02
Volume
62
Issue
4
Pages
1251-1259
ISSN
  • 0006-341X (ISSN-L)
  • 1541-0420
OpenAlex
W2067545994
Cited by
88
References
0
Citations by year
2026: 3 · 2025: 4 · 2024: 4 · 2023: 16 · 2022: 8 · 2021: 2 · 2020: 7 · 2018: 6 · 2017: 2 · 2016: 2 · 2015: 3 · 2014: 1 · 2013: 4 · 2012: 7
FWCI
3.12
Type
journal article
Language
en
Open access
closed
Locations
  • Biometrics (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
National Eye Institute (EY12269, R01EY012269)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
Keywords
Mann-Whitney test, clustered data, intra-cluster correlation, variance correction, Wilcoxon signed-rank test, mixed models, statistical power, ocular itching, ocular allergy
MeSH terms
Biometry, Data Interpretation, Statistical, Eye Diseases, Humans, Pruritus, Models, Statistical, Cluster Analysis, Randomized Controlled Trials as Topic, Statistics, Nonparametric

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