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

Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

1.3K
Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects...
1.3K
Kruskal-Wallis Test01:19

Kruskal-Wallis Test

1.3K
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...
1.3K
Test for Homogeneity01:23

Test for Homogeneity

1.7K
The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
1.7K
Kendall's Tau Test01:16

Kendall's Tau Test

1.1K
Kendall's tau test, also known as the Kendall rank coefficient test, is a nonparametric method for assessing association between two variables. This test is particularly useful for identifying significant correlations when the distributions of the sample and population are unknown. Developed in 1938 by the British statistician Sir Maurice George Kendall, the tau coefficient (denoted as τ) serves as a rank correlation coefficient, with values ranging from -1 to +1.
A τ value of +1...
1.1K
Introduction to Test of Independence01:21

Introduction to Test of Independence

2.1K
In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
2.1K
Chi-square Distribution01:10

Chi-square Distribution

5.4K
How does one determine if bingo numbers are evenly distributed or if some numbers occurred with a greater frequency? Or if the types of movies people preferred were different across different age groups or if a coffee machine dispensed approximately the same amount of coffee each time. These questions can be addressed by conducting a hypothesis test. One distribution that can be used to find answers to such questions is known as the chi-square distribution. The chi-square distribution has...
5.4K

You might also read

Related Articles

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

Sort by
Same author

Overexpression of tumstatin in genetically modified megakaryocytes changes the proangiogenic effect of platelets.

Transfusion·2014
Same author

Re-evaluating the concept of "dominant/index tumor nodule" in multifocal prostate cancer.

Virchows Archiv : an international journal of pathology·2014
Same author

[Research on several times of abruptly changes in the ultrafast transient reflectivity in Co films].

Guang pu xue yu guang pu fen xi = Guang pu·2014
Same author

Orange fluorescent proteins constructed from cyanobacteriochromes chromophorylated with phycoerythrobilin.

Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology·2014
Same author

A uniformly oriented MFI membrane for improved CO₂ separation.

Angewandte Chemie (International ed. in English)·2014
Same author

A Powerful Test for Multivariate Normality.

Journal of applied statistics·2014

Related Experiment Video

Updated: May 3, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

6.3K

A note on the kappa statistic for clustered dichotomous data.

Ming Zhou1, Zhao Yang

  • 1Global Biometric Sciences, Bristol-Myers Squibb, Hopewell, NJ, 08534, U.S.A.

Statistics in Medicine
|February 4, 2014
PubMed
Summary

A new semi-parametric variance estimator improves kappa statistic calculations for clustered dichotomous data. This method offers efficient, non-simulation-based alternatives, performing well even with fewer clusters.

Keywords:
agreementclustered dichotomous dataconfidence intervalcoverage probabilitykappa statisticphysician-patients

More Related Videos

Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia
10:05

Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia

Published on: January 27, 2018

8.7K
Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

41.3K

Related Experiment Videos

Last Updated: May 3, 2026

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

6.3K
Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia
10:05

Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia

Published on: January 27, 2018

8.7K
Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

41.3K

Area of Science:

  • Statistics
  • Biostatistics
  • Psychometrics

Background:

  • The kappa statistic is crucial for inter-rater reliability assessment, especially with clustered dichotomous data.
  • Existing methods for calculating kappa statistic variance in clustered data have limitations.

Purpose of the Study:

  • To develop and evaluate a new semi-parametric variance estimator for the kappa statistic in clustered physician-patient dichotomous data.
  • To compare the performance of the proposed estimator against existing methods using Monte Carlo simulations.

Main Methods:

  • A simulation-based cluster bootstrap method was adapted to address the correlation structure of clustered data.
  • A novel semi-parametric variance estimator was developed using the delta method and considering the data's covariance structure.
  • Extensive Monte Carlo simulations were conducted to assess empirical coverage probability, root-mean-square error, and confidence interval width.

Main Results:

  • The proposed semi-parametric variance estimator performs well, even with a smaller number of clusters (K=25).
  • Variance estimators that ignore within-cluster dependence are inappropriate.
  • The new proposal and sampling-based delta method offer efficient, non-simulation-based alternatives to bootstrap methods.

Conclusions:

  • The new semi-parametric variance estimator is a reliable and efficient tool for analyzing kappa statistics in clustered dichotomous data.
  • The proposed method provides a practical alternative to bootstrap-based approaches, especially when computational efficiency is desired.
  • The findings are applicable to psychiatric research and other fields utilizing clustered dichotomous outcome measures.