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Journal ArticleDOI

The Wilcoxon signed rank test for paired comparisons of clustered data.

Bernard Rosner, +2 more
- 01 Mar 2006 - 
- Vol. 62, Iss: 1, pp 185-192
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TLDR
The Wilcoxon signed rank test is a frequently used nonparametric test for paired data based on independent units of analysis that is able to incorporate clustering and is shown to be asymptotically normal as the number of clusters becomes large, if the cluster size is bounded.
Abstract
The Wilcoxon signed rank test is a frequently used nonparametric test for paired data (e.g., consisting of pre- and posttreatment measurements) based on independent units of analysis. This test cannot be used for paired comparisons arising from clustered data (e.g., if paired comparisons are available for each of two eyes of an individual). To incorporate clustering, a generalization of the randomization test formulation for the signed rank test is proposed, where the unit of randomization is at the cluster level (e.g., person), while the individual paired units of analysis are at the subunit within cluster level (e.g., eye within person). An adjusted variance estimate of the signed rank test statistic is then derived, which can be used for either balanced (same number of subunits per cluster) or unbalanced (different number of subunits per cluster) data, with an exchangeable correlation structure, with or without tied values. The resulting test statistic is shown to be asymptotically normal as the number of clusters becomes large, if the cluster size is bounded. Simulation studies are performed based on simulating correlated ranked data from a signed log-normal distribution. These studies indicate appropriate type I error for data sets with > or =20 clusters and a superior power profile compared with either the ordinary signed rank test based on the average cluster difference score or the multivariate signed rank test of Puri and Sen. Finally, the methods are illustrated with two data sets, (i) an ophthalmologic data set involving a comparison of electroretinogram (ERG) data in retinitis pigmentosa (RP) patients before and after undergoing an experimental surgical procedure, and (ii) a nutritional data set based on a randomized prospective study of nutritional supplements in RP patients where vitamin E intake outside of study capsules is compared before and after randomization to monitor compliance with nutritional protocols.

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Timing of State and Territorial COVID-19 Stay-at-Home Orders and Changes in Population Movement — United States, March 1–May 31, 2020

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Statistical guidelines for the analysis of data obtained from one or both eyes.

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A Study of Clustered Data and Approaches to Its Analysis

TL;DR: This work provides a statistical model for intracluster correlation and systematically investigate a range of methods for analyzing clustered data, revealing that it is critical to take data clustering into account and suggests appropriate statistical approaches that can be used to account for data clusters.
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A Data-Characteristic-Aware Latent Factor Model for Web Services QoS Prediction

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References
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Journal ArticleDOI

Longitudinal data analysis using generalized linear models

TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.
Book ChapterDOI

Individual Comparisons by Ranking Methods

TL;DR: The comparison of two treatments generally falls into one of the following two categories: (a) a number of replications for each of the two treatments, which are unpaired, or (b) we may have a series of paired comparisons, some of which may be positive and some negative as mentioned in this paper.
Book

Probability theory

Michel Loève
TL;DR: These notes cover the basic definitions of discrete probability theory, and then present some results including Bayes' rule, inclusion-exclusion formula, Chebyshev's inequality, and the weak law of large numbers.
Book

Probability Theory I

Michel Loève
Book

Nonparametrics: Statistical Methods Based on Ranks

TL;DR: Rank Tests for Comparing Two Treatments and Blocked Comparisons for two Treatments in a Population Model and the One-Sample Problem as discussed by the authors were used to compare more than two treatments.
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