Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Wilcoxon Signed-Ranks Test for Matched Pairs01:09

Wilcoxon Signed-Ranks Test for Matched Pairs

The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
Wilcoxon Rank-Sum Test01:21

Wilcoxon Rank-Sum Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a nonparametric test used to determine if there is a significant difference between the distributions of two independent samples. This test is designed specifically for two independent populations and has the following key requirements:
Wilcoxon Signed-Ranks Test for Median of Single Population01:14

Wilcoxon Signed-Ranks Test for Median of Single Population

The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures from...
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
Kruskal-Wallis Test01:19

Kruskal-Wallis Test

The Kruskal-Wallis test, also known as the Kruskal-Wallis H test, serves as a nonparametric alternative to the one-way ANOVA, offering a solution for analyzing the differences across three or more independent groups based on a single, ordinal-dependent variable. This statistical test is particularly valuable in scenarios where the data does not meet the normal distribution assumption required by its parametric counterparts. Kruskal-Wallis test is designed typically to handle ordinal data or...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Analysis of Stepped-Wedge Cluster Randomized Trials: A Tutorial Using Marginal Models.

Statistics in medicine·2026
Same author

A Pharmacist Consultant Service for Deprescribing Opioids and Benzodiazepines in Older Adults: A Cluster Randomized Trial.

JAMA network open·2026
Same author

Inflammasome targeting for periodontitis prevention is sex dependent.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Mouth Care Without a Battle: Change in Assisted Living Staff Self-Efficacy and Attitudes.

Journal of the American Medical Directors Association·2025
Same author

Preparedness for care transitions to home and acute care use of skilled nursing facility patients.

BMC geriatrics·2025
Same author

Predictors of new persistent opioid use after surgery in adults.

Anesthesiology and perioperative science·2025
Same journal

An Adaptive Biomarker-based Umbrella Trial Design Using Bayesian Latent Class Model.

Statistics in biopharmaceutical research·2026
Same journal

A Bayesian Adaptive Marker-Stratified Design for Phase II Clinical Trials Using Calibrated Spike-and-Slab priors.

Statistics in biopharmaceutical research·2026
Same journal

On the Two-Step Hybrid Design for Augmenting Randomized Trials Using Real-World Data.

Statistics in biopharmaceutical research·2025
Same journal

Two-stage Adaptive Enrichment Designs with Survival Outcomes and Adjustment for Misclassification in Predictive Biomarkers.

Statistics in biopharmaceutical research·2025
Same journal

A novel longitudinal rank-sum test for multiple primary endpoints in clinical trials: Applications to neurodegenerative disorders.

Statistics in biopharmaceutical research·2025
Same journal

Isotonic Phase I cancer clinical trial design utilizing patient-reported outcomes.

Statistics in biopharmaceutical research·2025
See all related articles

Related Experiment Video

Updated: May 28, 2026

Effects of Mechanical Methods Used in Peri-implantitis Treatment on Implant Surface Decontamination and Roughness
06:36

Effects of Mechanical Methods Used in Peri-implantitis Treatment on Implant Surface Decontamination and Roughness

Published on: March 14, 2025

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics.

John S Preisser1, Pranab K Sen, Steven Offenbacher

  • 1John S. Preisser, is Research Professor, and Pranab K. Sen, is Cary C. Boshamer Distinguished Professor, Department of Biostatistics, and Steven Offenbacher, DDS, PhD, MMSc, is OraPharma Distinguished Professor of Periodontal Medicine, Director, Center for Oral and Systemic Diseases, North Carolina Oral Health Institute, University of North Carolina at Chapel Hill.

Statistics in Biopharmaceutical Research
|October 11, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces nonparametric statistical methods for analyzing longitudinal biomarker data in dental research, particularly for small sample sizes. These methods effectively identify changes over time in inflammation markers, aiding periodontal research.

Related Experiment Videos

Last Updated: May 28, 2026

Effects of Mechanical Methods Used in Peri-implantitis Treatment on Implant Surface Decontamination and Roughness
06:36

Effects of Mechanical Methods Used in Peri-implantitis Treatment on Implant Surface Decontamination and Roughness

Published on: March 14, 2025

Area of Science:

  • Dental research
  • Periodontal research
  • Biomarker analysis

Background:

  • Multivariate parametric methods are sensitive to outliers and deviations from Gaussian assumptions in small sample sizes.
  • Periodontal research often analyzes molecular mediators of inflammation, requiring robust statistical approaches.
  • Controlling error rates in multiple hypothesis testing is crucial for reliable biomarker identification.

Purpose of the Study:

  • To review and apply univariate and multivariate nonparametric hypothesis tests for longitudinal data.
  • To assess changes over time in 31 biomarkers from gingival crevicular fluid.
  • To identify biomarkers that exhibit induced changes in response to experimental conditions.

Main Methods:

  • Application of nonparametric hypothesis tests to longitudinal data from 22 subjects.
  • Utilizing multivariate Wilcoxon signed rank tests on area under the curve summary measures for each biomarker.
  • Comparison of multivariate nonparametric tests with their univariate counterparts.
  • Examination of multiple hypothesis testing methods, including false discovery rate and family-wise error rate control.

Main Results:

  • Nonparametric methods were applied to analyze changes in 31 biomarkers over time in response to induced gingivitis.
  • Multivariate Wilcoxon signed rank tests identified significant changes in specific biomarkers.
  • The study compared the efficacy of multivariate versus univariate nonparametric approaches.

Conclusions:

  • Nonparametric methods offer a robust alternative to parametric approaches for analyzing longitudinal biomarker data in dental and periodontal research with small sample sizes.
  • The applied methods effectively detect changes in inflammation biomarkers.
  • Proper control of multiple hypothesis testing is essential for accurate interpretation of biomarker data.