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...
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...
Censoring Survival Data01:09

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...
Ranks01:02

Ranks

Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a survival tree begins...
How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...

You might also read

Related Articles

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

Sort by
Same author

Asymptotically Correct Person Fit z-Statistics For the Rasch Testlet Model.

Psychometrika·2026
Same author

Asymptotically Correct Person Fit z-Statistics For the Rasch Testlet Model.

Psychometrika·2024
Same author

Author Correction: Skill levels and gains in university STEM education in China, India, Russia and the United States.

Nature human behaviour·2021
Same author

Skill levels and gains in university STEM education in China, India, Russia and the United States.

Nature human behaviour·2021
Same author

Computer science skills across China, India, Russia, and the United States.

Proceedings of the National Academy of Sciences of the United States of America·2019
Same author

CFA Models with a General Factor and Multiple Sets of Secondary Factors.

Psychometrika·2018
Same journal

Planned missingness in intensive longitudinal studies: Extensions and comparisons of multiform designs.

Behavior research methods·2026
Same journal

A validity-guided workflow for robust large language model research in psychology.

Behavior research methods·2026
Same journal

Are 7-point Likert scales preferable to 5-point scales in language research?

Behavior research methods·2026
Same journal

Generative psychometrics via AI-GENIE: Automatic item generation and validation with network-integrated evaluation.

Behavior research methods·2026
Same journal

Exploring psychological tradeoffs: Developing and demonstrating an R Shiny app for Pareto optimization.

Behavior research methods·2026
Same journal

The performance of Bayesian fit measures in detecting misspecified multilevel structural equation modeling.

Behavior research methods·2026
See all related articles

Related Experiment Video

Updated: Jul 4, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

A modified procedure for parallel analysis of ordered categorical data.

Ou Lydia Liu1, Frank Rijmen

  • 1Educational Testing Service, Princeton, New Jersey, USA. lliu@ets.org

Behavior Research Methods
|June 5, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces a modified parallel analysis procedure to improve factor retention accuracy for ordinal variables, addressing limitations of the O'Connor method. The enhanced technique better approximates ordinal data by considering variable frequency distributions.

Related Experiment Videos

Last Updated: Jul 4, 2026

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
11:09

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

Published on: July 17, 2021

Area of Science:

  • Psychometrics
  • Statistical analysis

Background:

  • Parallel analysis is a robust method for determining the number of factors in exploratory factor analysis.
  • The O'Connor (2000) parallel analysis procedure is widely used but has limitations with missing data and ordinal variables.

Purpose of the Study:

  • To adapt and modify the O'Connor parallel analysis procedure.
  • To provide an alternative method that better approximates ordinal data.

Main Methods:

  • Modified the O'Connor parallel analysis procedure.
  • Incorporated variable frequency distributions, including response categories and their frequencies, to better approximate ordinal data.

Main Results:

  • The modified procedure offers an alternative to the O'Connor procedure for handling ordinal variables.
  • Theoretical and practical differences between the two methods are discussed.

Conclusions:

  • The adapted parallel analysis procedure provides a more accurate approach for factor retention with ordinal data.
  • SAS syntax for the modified procedure is provided for practical implementation.