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

Bonferroni Test01:10

Bonferroni Test

3.5K
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...
3.5K
Kendall's Coefficient of Concordance01:20

Kendall's Coefficient of Concordance

1.2K
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...
1.2K
Confidence Coefficient01:24

Confidence Coefficient

10.9K
The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
10.9K
Spearman's Rank Correlation Test01:20

Spearman's Rank Correlation Test

1.6K
Spearman's rank correlation test, also known as Spearman's rho, is a nonparametric method for assessing the strength and direction of association between two variables. This test is particularly valuable when the data distribution is unknown or when the assumption of normality does not hold. Named after the English psychologist and statistician Dr. Charles Edward Spearman, it serves as the nonparametric counterpart to Pearson's correlation coefficient.
Spearman's test calculates correlation by...
1.6K
McNemar's Test01:23

McNemar's Test

974
McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...
974
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

641
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...
641

You might also read

Related Articles

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

Sort by
Same journal

Handling Missing Data in Intensive Longitudinal Data with Mixed Missing Mechanisms.

Multivariate behavioral research·2026
Same journal

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Multivariate behavioral research·2026
Same journal

A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments.

Multivariate behavioral research·2026
Same journal

Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions.

Multivariate behavioral research·2026
Same journal

A Modularized Higher-Order Diagnostic Classification Model for Clustered Attribute Hierarchies.

Multivariate behavioral research·2026
Same journal

Generalizing Causal Effects to a Target Population Without Individual-Level Data from the Target Population.

Multivariate behavioral research·2026

Related Experiment Video

Updated: Mar 26, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

Published on: August 28, 2021

5.1K

A Nonparametric Coefficient Of Internal Consistency.

R R Trippi, R B Settle

    Multivariate Behavioral Research
    |January 26, 2016
    PubMed
    Summary

    This study introduces coefficient alphaτ, a new nonparametric measure for assessing internal test consistency. It enables significance testing for differences in consistency across various conditions and supports tests with nominal scale data.

    Area of Science:

    • Psychometrics
    • Psychological Measurement
    • Statistical Analysis

    Background:

    • Assessing internal test consistency is crucial for reliable psychological measurement.
    • Existing methods may have limitations with certain data types or test structures.
    • Need for flexible and robust measures of internal consistency.

    Purpose of the Study:

    • Introduce coefficient alphaτ, a novel frequency-based, nonparametric measure of internal test consistency.
    • Enable facile measurement of significance in internal consistency differences.
    • Facilitate analysis of psychological tests with nominal scale data.

    Main Methods:

    • Development of a frequency-based, nonparametric statistical measure.
    • Application to internal test consistency analysis.

    More Related Videos

    Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
    09:00

    Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

    Published on: August 16, 2024

    1.3K
    A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing
    15:00

    A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing

    Published on: February 7, 2025

    1.2K

    Related Experiment Videos

    Last Updated: Mar 26, 2026

    Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA
    10:58

    Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics BM-PROMA

    Published on: August 28, 2021

    5.1K
    Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education
    09:00

    Author Spotlight: Validation of SICOLE-R for Assessing Cognitive and Reading Skills in Spanish-Speaking Children and Its Role in Personalized Education

    Published on: August 16, 2024

    1.3K
    A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing
    15:00

    A Tablet-Based Curriculum-Based Measurement Protocol for Kindergarten Writing

    Published on: February 7, 2025

    1.2K
  • Designed for tests with discrete response categories (nominal data).

    • Main Results:

    • Coefficient alphaτ provides a method for significance testing of internal consistency.
    • The measure is applicable to psychological tests yielding nominal scale data.
    • Supports the incorporation of multiple dimensions within single test items.

    Conclusions:

    • Coefficient alphaτ offers a flexible and powerful tool for psychometric analysis.
    • Enhances test construction by accommodating diverse item types and structures.
    • Improves the ability to compare internal consistency across different testing scenarios.