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

Determination of Expected Frequency01:08

Determination of Expected Frequency

2.5K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.5K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

6.6K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
6.6K
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

439
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...
439
Two-Way ANOVA01:17

Two-Way ANOVA

3.2K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
3.2K
Relative Frequency Histogram01:14

Relative Frequency Histogram

6.2K
The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
6.2K
Statistical Methods to Analyze Parametric Data: ANOVA01:12

Statistical Methods to Analyze Parametric Data: ANOVA

1.4K
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
1.4K

You might also read

Related Articles

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

Sort by
Same author

Evaluating the Swedish Occupational Fatigue Inventory (SOFI) Among Providers in a Pediatric Emergency Department.

IISE transactions on occupational ergonomics and human factors·2026
Same author

Laypeople's Perceptions of Clinician Performance Metrics Based on Cancer Screening Attendance.

JAMA health forum·2026
Same author

Outcomes for Labor Induction Compared With Expectant Management Among Women Receiving Hospital-Based, Midwifery-Led Care.

Journal of midwifery & women's health·2026
Same author

Guidance for the Methodological Challenges of Polytobacco Use in Tobacco Regulatory Science.

Public health reports (Washington, D.C. : 1974)·2025
Same author

Apolipoprotein E, Executive Function, and Falls across Cognitive Status: A Cross-Sectional Study.

Dementia and geriatric cognitive disorders·2025
Same author

Qualitative Mediation Analysis: an Important Method for Exploring Mediating Mechanisms in Prevention Science.

Prevention science : the official journal of the Society for Prevention Research·2025

Related Experiment Video

Updated: Dec 26, 2025

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling
06:04

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling

Published on: January 17, 2025

1.2K

Statistical Evaluation of Person-Oriented Mediation Using Configural Frequency Analysis.

Heather L Smyth1, David P MacKinnon2

  • 1Department of Psychology, Arizona State University, Tempe, AZ, USA. Heather.Smyth@asu.edu.

Integrative Psychological & Behavioral Science
|March 20, 2020
PubMed
Summary

Configural frequency mediation offers a person-oriented approach to understanding causal relationships. An adapted joint significance test shows adequate performance, addressing issues with the traditional method.

Keywords:
Configural frequency analysisMediationPerson-centeredPerson-oriented

More Related Videos

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.2K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.3K

Related Experiment Videos

Last Updated: Dec 26, 2025

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling
06:04

Functional Near-Infrared Spectroscopy Hyperscanning Study in Psychological Counseling

Published on: January 17, 2025

1.2K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.2K
Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

4.3K

Area of Science:

  • Psychology
  • Statistics
  • Causal Inference

Background:

  • Mediation analysis explains variable relationships, typically for populations.
  • Researchers often need to infer causal processes for individuals or small groups.
  • Person-oriented approaches focus on individual differences, offering a complementary perspective.

Purpose of the Study:

  • To clarify and evaluate configural frequency mediation (CFM).
  • To compare CFM with traditional variable-oriented mediation analysis.
  • To develop and assess an improved CFM approach using a joint significance test.

Main Methods:

  • Log-linear modeling of contingency tables for configural frequency analysis.
  • Statistical simulation study comparing CFM and logistic regression.
  • Development and testing of a joint significance test for configural mediation.

Main Results:

  • Traditional configural frequency mediation analysis exhibited high Type I error rates.
  • An alternative configural mediation analysis based on a joint significance test demonstrated adequate performance.
  • Clarified decision rules for configural mediation analysis.

Conclusions:

  • Configural frequency mediation, while promising, requires methodological refinement.
  • A joint significance test approach improves the performance and reliability of configural mediation analysis.
  • This work provides clearer guidelines and a more robust method for person-oriented mediation analysis.