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 Experiment Videos

Item factor analysis: current approaches and future directions.

R J Wirth1, Michael C Edwards

  • 1L. L. Thurstone Psychometric Laboratory, Department of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3270, USA. rjwirth@unc.edu

Psychological Methods
|April 4, 2007
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

A patient-centered conceptual model and measurement framework for migraine experience developed by the Migraine Clinical Outcome Assessment System.

Headache·2026
Same author

The argument-based approach to validity: theory, assumptions, evidence, and consequences.

Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation·2026
Same author

Applying the Argument-Based Approach to Validation With Clinical Outcome Assessments: Strategies for Constructing a Rationale.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research·2026
Same author

Development and psychometric evaluation of a new self-report measure to assess patient engagement behaviours and capacity in the USA: the Patient Engagement Capacity Survey.

BMJ open·2025
Same author

Initial Psychometric Evaluation of the Barth Syndrome Symptom Assessment (BTHS-SA) for Adolescents and Adults in a Phase 2 Clinical Study.

Orphanet journal of rare diseases·2025
Same author

Symptoms across the phases of the migraine cycle from the patient's perspective: Results of the MiCOAS qualitative study.

Headache·2024
Same journal

Bayesian evaluation for latent variable models: A tutorial on computing information criteria and bayes factors with the r package bleval.

Psychological methods·2026
Same journal

A stochastic block prior for clustering in graphical models.

Psychological methods·2026
Same journal

Three-level vector autoregressive models.

Psychological methods·2026
Same journal

Scaling cognitive modeling to big data: A deep learning approach to studying individual differences in evidence accumulation model parameters.

Psychological methods·2026
Same journal

Best practices in multilevel modeling for within-cluster group comparisons: An evaluation of coding strategies reflecting group composition and heterogeneity.

Psychological methods·2026
Same journal

A unified framework for psychometrics in experimental psychology: The standardized generalized hierarchical factor model.

Psychological methods·2026
See all related articles

This study reviews item factor analysis (IFA) for categorical data, highlighting issues with traditional methods and exploring advanced estimation techniques like Markov chain Monte Carlo for complex models.

Area of Science:

  • Psychometrics
  • Statistical Modeling

Background:

  • Traditional factor analysis models are unsuitable for categorical data.
  • Item-level data, such as Likert scales, require specialized methods.

Purpose of the Study:

  • To review and synthesize the literature on item factor analysis (IFA) for ordered-categorical data.
  • To address challenges in estimating IFA models with numerous items and factors.
  • To present popular IFA models and discuss recent estimation developments.

Main Methods:

  • Review of structural equation modeling and item response theory literature.
  • Synthesis of estimation methods for ordered-categorical data.
  • Discussion of advanced techniques like Markov chain Monte Carlo (MCMC).

Related Experiment Videos

Main Results:

  • Existing continuous data methods are inadequate for categorical item data.
  • Popular IFA models and estimation techniques are presented.
  • Recent advancements in IFA parameter estimation are discussed.

Conclusions:

  • Item factor analysis (IFA) requires specific methods for categorical data.
  • Advanced estimation techniques are crucial for complex IFA models.
  • Guidance is provided for future research and applied researchers.