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

Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
Impact of Groups on Groups01:19

Impact of Groups on Groups

Social psychologists analyze how groups influence one another, shaping social structures and interactions through both cooperation and competition. These dynamics manifest in various ways, ranging from economic partnerships to intergroup conflicts that shape societal structures and perceptions.Cooperation and Competition in Intergroup RelationsIntergroup relationships vary across contexts, sometimes fostering cooperation and mutual benefit while at other times leading to conflict and...
Methods of Medium Optimization01:28

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...
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...
Causes of Similarity-Dissimilarity Effect01:26

Causes of Similarity-Dissimilarity Effect

The similarity-dissimilarity effect, a fundamental concept in social psychology, explains how interpersonal similarities and differences influence attraction and social interactions. This effect is supported by three key psychological perspectives: balance theory, social comparison theory, and consensual validation.Balance Theory and Cognitive ConsistencyBalance theory, developed by Fritz Heider, posits that individuals seek cognitive consistency in their relationships. When two people share...
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...

You might also read

Related Articles

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

Sort by
Same author

Advancing Dimensional Models of Psychopathology in Cancer: Insights From Applying the Hierarchical Taxonomy of Psychopathology (HiTOP).

Psycho-oncology·2026
Same author

The Impact of Family Factors on Adolescent Intensive Outpatient Psychotherapy Outcomes for Suicidal Thoughts, Behaviors, and Depression.

Suicide & life-threatening behavior·2026
Same author

Distinct Event-Related-Potential Biomarkers of Broad Versus Specific Dimensions of the Hierarchical Taxonomy of Psychopathology Externalizing Spectrum.

Clinical psychological science : a journal of the Association for Psychological Science·2026
Same author

Patterns of smartphone typing performance by time awake: implications for unobtrusive ambulatory mental fatigue assessment.

PLOS digital health·2026
Same author

A Randomized Controlled Trial Comparing Two Treatments for Vulnerable and Grandiose Narcissism: Unified Protocol vs. Schema-Focused Therapy.

Clinical psychology & psychotherapy·2026
Same author

Structure of current psychopathology and its associations with daily life experiences using the Hierarchical Taxonomy of Psychopathology Self-Report (HiTOP-SR) in a mixed clinical/community sample.

Psychological assessment·2026

Related Experiment Video

Updated: Jun 17, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

Integrating methods to optimize circumplex description and comparison of groups.

Aidan G C Wright1, Aaron L Pincus, David E Conroy

  • 1Department of Psychology, The Pennsylvania State University, University Park, PA 16802, USA. aidan@psu.edu

Journal of Personality Assessment
|December 18, 2009
PubMed
Summary

This study introduces circular statistics and the structural summary method for analyzing group data from circumplex assessments. Combining these methods offers richer insights into interpersonal dynamics and group profiles.

More Related Videos

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

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Related Experiment Videos

Last Updated: Jun 17, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

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

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Area of Science:

  • Psychological Measurement
  • Quantitative Psychology
  • Social Psychology

Background:

  • Circumplex models are widely used in personality and social psychology.
  • Existing methods for analyzing group-level circumplex data have limitations.
  • Integrating diverse statistical approaches can enhance data interpretation.

Purpose of the Study:

  • To provide a methodological guide for integrating group description and comparison techniques for circumplex assessment instruments.
  • To demonstrate the utility of circular statistics and the structural summary method for analyzing group data.
  • To highlight the complementary nature of these statistical approaches.

Main Methods:

  • Application of circular statistics (e.g., mean, variance, confidence intervals) to circumplex data.
  • Utilization of the structural summary method to assess profile characteristics (e.g., prototypicality, differentiation).
  • Comparative analysis of group data using both circular statistics and the structural summary method.

Main Results:

  • Circular statistics provide parameters analogous to linear equivalents, offering insights into theme and homogeneity.
  • The structural summary method yields complementary data on profile prototypicality, differentiation, and thematic content.
  • Combined application of both methods yields more comprehensive information than either alone.

Conclusions:

  • Circular statistics and the structural summary method are valuable tools for group-level analysis of circumplex measures.
  • These methods enhance the understanding of interpersonal dynamics and group profiles.
  • The approach is generalizable to other domains utilizing circumplex models, such as emotion and vocational preference.