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Area of Science:

  • Psychology
  • Quantitative Psychology
  • Psychometrics

Background:

  • Confirmatory factor analysis (CFA) is a key method for developing psychological measurement models.
  • Evaluating CFA model fit is complex due to exact fit tests and absolute interpretation challenges of fit indices.
  • Established cutoff rules for fit indices lack universal applicability and context-specific tailoring.

Purpose of the Study:

  • To review and critically evaluate the reporting and application of model fit indices in CFA within psychological research.
  • To compare reported fit index values against established cutoff rules.
  • To reevaluate model fit using novel methods with tailored, data-driven cutoff criteria.

Main Methods:

  • Systematic review of all CFA models published in *Psychological Assessment* from 2015 to 2020.
  • Comparison of reported fit index values with existing cutoff criteria.
  • Reevaluation of model fit using newly developed methods with model- and data-specific cutoffs.

Main Results:

  • Many studies exhibited questionable model fit, particularly concerning independent cluster constraints.
  • A significant number of studies failed to report all necessary information for independent reevaluation of model fit.
  • Newly developed methods highlighted discrepancies when compared to traditional fit index evaluations.

Conclusions:

  • The evaluation of model fit in many published CFA studies requires critical scrutiny.
  • Incomplete reporting practices hinder robust assessment and replication of CFA model fit.
  • Advances in model fit evaluation necessitate updated approaches and reporting standards.