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

Comparative fit indexes in structural models.

P M Bentler1

  • 1Department of Psychology, University of California, Los Angeles 90024-1563.

Psychological Bulletin
|March 1, 1990
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

Invariant Standardized Estimated Parameter Change for Model Modification in Covariance Structure Analysis.

Multivariate behavioral research·2016
Same author

A NEW MATRIX FOR THE ASSESSMENT OF FACTOR CONTRIBUTIONS.

Multivariate behavioral research·2016
Same author

Brief Report: An Additional Minimal Transformation To Orthonormality.

Multivariate behavioral research·2016
Same author

The Relationship Of Personality Structure To Patterns Of Adolescent Substance Use.

Multivariate behavioral research·2016
Same author

Interrelations Among Models For The Analysis Of Moment Structures.

Multivariate behavioral research·2016
Same author

Longitudinal Analysis Of The Role Of Peer Support, Adult Models, And Peer Subcultures In Beginning Adolescent Substance Use: An Application Of Setwise Canonical Correlation Methods.

Multivariate behavioral research·2016
Same journal

Does the variance of personality traits change across the lifespan? A meta-analytic review of longitudinal studies.

Psychological bulletin·2026
Same journal

Artificial intelligence as a partner in meta-analysis-Research agenda, user recommendations, and speed-accuracy tradeoffs: Commentary on Jansen et al. (2025).

Psychological bulletin·2026
Same journal

Relationships between cognition and daily functioning in adults with bipolar disorder: A systematic review and multilevel meta-analysis.

Psychological bulletin·2026
Same journal

The association between reading anxiety and reading achievement: A meta-analysis and systematic review.

Psychological bulletin·2026
Same journal

Perfectionism is accelerating over time: A cross-temporal meta-analytic review of 35 years of college student data.

Psychological bulletin·2026
Same journal

High math anxiety is associated with lower math achievement across 90 countries: An individual participant data meta-analysis of representative student and adult samples.

Psychological bulletin·2026
See all related articles

New comparative fit index (CFI) and fit index (FI) coefficients improve structural model evaluation by addressing limitations in existing fit indexes, performing well across all sample sizes.

Area of Science:

  • Statistics
  • Psychometrics
  • Quantitative Psychology

Background:

  • Structural equation modeling (SEM) relies on fit indexes to assess model adequacy.
  • Existing fit indexes often fail to estimate population parameters and can be biased in small samples.

Purpose of the Study:

  • Introduce novel normed (CFI) and nonnormed (FI) fit indexes for structural models.
  • Improve upon existing normed fit index (NFI) and non-normed fit index (NNFI) by addressing their known limitations.

Main Methods:

  • Propose a new coefficient summarizing relative reduction in noncentrality parameters for nested models.
  • Develop two estimators for this coefficient, yielding CFI and FI.
  • Generalize index computation for Wald and Lagrange multiplier statistics.

Related Experiment Videos

Main Results:

  • CFI corrects for underestimation of fit in small samples common with NFI.
  • FI mitigates extreme under- or overestimation issues found in NNFI.
  • New indexes (CFI, FI) demonstrate robust performance across all sample sizes, outperforming NFI and NNFI.

Conclusions:

  • CFI and FI offer improved, reliable measures for evaluating structural model fit.
  • The proposed indexes provide better estimates of model fit, particularly in small samples.
  • These advancements enhance the utility of fit indexes in structural equation modeling.