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

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...
Bonferroni Test01:10

Bonferroni Test

The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
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...
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:
Multiple Comparison Tests01:13

Multiple Comparison Tests

Multiple comparison test, abbreviated as MCT, is a post hoc analysis generally performed after comparing multiple samples with one or more tests. An MCT will help identify a significantly different sample among multiple samples or a factor among multiple factors.
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
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...

You might also read

Related Articles

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

Sort by
Same author

Correction: Do altmetrics correlate with the quality of papers? A large-scale empirical study based on F1000Prime data.

PloS one·2025
Same author

Corrigendum for 'The influence of public policy and administration expertise on policy: an empirical study' by Robin Haunschild, Kate Williams and Lutz Bornmann.

Evidence & policy : a journal of research, debate and practice·2025
Same author

The influence of public policy and administration expertise on policy: an empirical study.

Evidence & policy : a journal of research, debate and practice·2025
Same author

Are quality assessments in science affected by anchoring effects? - Empirical results from a survey of authors assessing previously cited papers.

PloS one·2025
Same author

The use of OpenAlex to produce meaningful bibliometric global overlay maps of science on the individual, institutional, and national levels.

PloS one·2024
Same author

The costs of competition in distributing scarce research funds.

Proceedings of the National Academy of Sciences of the United States of America·2024

Related Experiment Video

Updated: May 19, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
10:39

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

Testing differences statistically with the Leiden ranking.

Loet Leydesdorff, Lutz Bornmann

    Scientometrics
    |August 21, 2012
    PubMed
    Summary
    This summary is machine-generated.

    The Leiden ranking introduces a new indicator, Proportion of Top-10% Publications, to statistically assess university performance differences. This method enhances the reliability of university comparisons.

    More Related Videos

    Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
    05:58

    Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

    Published on: March 22, 2022

    Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
    07:13

    Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

    Published on: April 18, 2025

    Related Experiment Videos

    Last Updated: May 19, 2026

    Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
    10:39

    Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

    Published on: August 29, 2025

    Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
    05:58

    Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes

    Published on: March 22, 2022

    Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
    07:13

    Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model

    Published on: April 18, 2025

    Area of Science:

    • Bibliometrics
    • Higher Education Research
    • Scientific Impact Assessment

    Background:

    • The Leiden ranking is a widely recognized system for evaluating university performance.
    • Traditional metrics may not fully capture the impact or excellence of research output.
    • A need exists for more robust indicators to compare academic institutions.

    Purpose of the Study:

    • To introduce and validate the Proportion of Top-10% Publications (PP(top-10%)) as a novel indicator in the Leiden ranking.
    • To enable statistically significant comparisons of research performance between universities.
    • To enhance the precision of university impact assessments.

    Main Methods:

    • Utilizing publication data from the Leiden ranking 2011/2012.
    • Calculating the Proportion of Top-10% Publications (PP(top-10%)) for various institutions.
    • Applying statistical methods to test performance differences indicated by PP(top-10%).

    Main Results:

    • The PP(top-10%) indicator was successfully implemented in the 2011/2012 Leiden ranking.
    • This indicator provides a statistically sound basis for comparing the research performance of universities.
    • The new metric allows for more reliable identification of leading institutions in terms of high-impact publications.

    Conclusions:

    • The Proportion of Top-10% Publications is a valuable addition to university ranking methodologies.
    • This indicator offers a statistically robust measure for assessing research excellence and impact.
    • The Leiden ranking's use of PP(top-10%) improves the accuracy of international university comparisons.