Cut-off value of the fit indices in Confirmatory Factor Analysis.

Federico Maximiliano Jordan Muiños

Abstract


In psychological research, it is of great relevance to know whether the questionnaires used measure the latent constructs of interest. For this purpose, Confirmatory Factor Analysis is frequently used in the specialized literature to provide evidence of validity to the scales used. However, there is currently a certain disparity in the criteria regarding the cut-off points to be taken into consideration. For this reason, this paper aims to review the literature on the different cut-off points for the most commonly used fit indexes. It is concluded that to select the indexes and interpret the results, it should be should take into account that these cut-off points may change for different reasons, such as sample size

Keywords


cut point; fit indices; confirmatory factor analysis; validity



DOI: https://doi.org/10.62174/psocial.6764

References


Batista-Foguet, J. M., Coenders, G., & Alonso, J. (2004). Análisis factorial confirmatorio. Su utilidad en la validación de cuestionarios relacionados con la salud. Medicina Clínica, 122 (1), 21-7. https://doi.org/10.1157/13057542

Brown, T. (2015). Confirmatory factor analysis for applied research, Second Edition. New York: Guilford Press.

Cadena-Iñiguez, P., Rendón-Medel, R., Aguilar-Ávila, J., Salinas-Cruz, E., del Rosario de la Cruz-Morales, F., & Sangerman-Jarquín , D. M. (2017). Métodos cuantitativos, métodos cualitativos o su combinación en la investigación: un acercamiento en las ciencias sociales. Revista Mexicana de Ciencias Agrícolas, 8 (7), 1603 - 1617.

Chen, F. F. (2007). Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance. Structural Equation Modeling, 14 (3), 464 - 504. https://doi.org/10.1080/10705510701301834

Cho, G., Hwang, H., Sarstedt, M., & Ringle, Ch. M. (2020). Cutoff criteria for overall model fit indexes in generalized structured component analysis. Journal of Marketing Analytics. https://doi.org/10.1057/s41270-020-00089-1

Curran, P. J., Bollen, K. A., Chen, F., Paxton, P., & Kirby, J. B. (2003). Finite Sampling Properties of the Point Estimates and Confidence Intervals of the RMSEA. Sociological Methods & Research, 32 (2), 208 - 252. https://doi.org/10.1177/0049124103256130

Domínguez-Lara, S. (2019). Correlación entre residuales en análisis factorial confirmatorio: una breve guía para su uso e interpretación. Interacciones, 5 (3), 1 - 7. https://doi.org/10.24016/2019.v5n3.207

Escobedo Portillo, M. T., Hernández Gómez, J. A., Estebané Ortega, V. E., & Martínez Moreno, G. (2016). Modelos de ecuaciones estructurales: características, fases, construcción, aplicación y resultados. Ciencia y Trabajo, 18 (55), 16-22. https://doi.org/10.4067/S0718-24492016000100004

Hernández Sampieri, R., Fernández Collado, C., Baptista Lucio, M. P. (2014). Metodología de la Investigación (Sexta Edición). Mc Graw Hill Education.

Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6 (1), 1 – 55. https://doi.org/10.1080/10705519909540118

Kamp, K, Wyatt, G., Dudley-Brown, S., Brittain, K., & Given, B. (2018). Using cognitive interviewing to improve questionnaires: An exemplar study focusing on individual and condition-specific factors. Applied Nursing Research. https://doi.org/10.1016/j.apnr.2018.06.007

Kline, R. B. (2011). Principles and practice of structural equiation modeling (Third Edition). The Guilford Press.

Kretzschmar, A., & Gignac, G. E. (2019). At what sample size do latent variable correlations stabilize? Journal of Research in Personality, 80, 17 - 22. https://doi.org/10.1016/j.jrp.2019.03.007

Lai, K. (2020). Fit Difference Between Nonnested Models Given Categorical Data: Measures and Estimation. Structural Equation Modeling: A Multidisciplinary Journal, https://doi.org/10.1080/10705511.2020.1763802

Lewis, T. F. (2017). Evidence Regarding the Internal Structure: Confirmatory Factor Analysis. Measurement and Evaluation in Counseling and Development. https://doi.org/10.1080/07481756.2017.1336929

McNish, D., An, J., & Hancock, G. R. (2017). The Thorny Relation Between Measurement Quality and Fit Index Cutoffs in Latent Variable Models. Journal of personality assessment. https://doi.org/10.1080/00223891.2017.1281286

Shi, D., & Maydeu-Olivares (2019). The Effect of Estimation Methods on SEM Fit Indices. Educational and Psychological Measurement, 1 - 25. https://doi.org/10.1177/0013164419885164

Shi, D., Maydeu-Olivares, A., & Rosseel, Y. (2019). Assessing Fit in Ordinal Factor Analysis Models: SRMR vs. RMSEA. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705511.2019.1611434

Smith, T. D., & McMillan, B. F. (2001) Primer of Model Fit Indices in Structural Equation Modeling. Artículo presentado en Southwest Educational Research Association.

Walker, D. A., & Smith, T. J. (2017). Computing Robust, Bootstrap-Adjusted Fit Indices for Use With Nonnormal Data. Measurement and Evaluation in Counseling and Development, 50, 131 - 137. https://doi.org/10.1080/07481756.2017.1326748

Wu, H., & Leung, S. O. (2017). Can Likert Scales be Treated as Interval Scales?—A Simulation Study. Journal of Social Service Research, 43 (4), 527 - 532. https://doi.org/10.1080/01488376.2017.1329775

Xia, Y., & Yang, Y. (2019). RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Behavior Research Method, 51, 409 - 428. https://doi.org/10.3758/s13428-018-1055-2


Refbacks

  • There are currently no refbacks.


Estadísticas
Visitas al Abstract:979
PDF (Español (España)):2342
EPUB (Español (España)):57
HTML (Español (España)):320
XML (Español (España)):202


{PSOCIAL} Journal of Research in Social Psychology. Faculty of Social Sciences | University of Buenos Aires (UBA)

ISSN 2422-619X. Semiannual publication (January-June and July-December).
 
Design: Mae Bermudez
 
 Jorunal Indexed and listed in:
  • ERIH PLUS (European Reference Index for the Humanities and Social Sciences) [registry]
  • Latindex Catálogo 2.0 (Regional Cooperative Online Information System for Scholarly Journals from Latin America, the Caribbean, Spain and Portuga) [registry]
  • DOAJ (Directory Open Access Journals) [registry]
  • MIAR (Information Matrix for the Analysis of Journals) [registry]
  • PSICODOC (Online Bibliographic Database Madrid Official College of Psychologists) [registry] 
  • RDIUBA (Institutional Digital Repository) [registry]
  • REDIB (Iberoamerican Network for Innovation and Scientific Knowledge) [registry]
  • Open AIRE (Open Access Infraestructure for Research in Europe) [registry] 
  • Red LatinRev / FLACSO library (Latin American Faculty of Social Sciences) [registry]
  • BINPAR (National Bibliography of Registered Periodicals) [registry]
  • LATINOAMERICANA (Association of Academic Journals of Humanities and Social Sciences) [registry]
  • CLASE (Latin-American Citations in Social Sciences and Humanities) [registry]
  • Sherpa Romeo [registry]
  • Basic Nucleus of Argentine Scientific Journals [registry]
  • Mirab@l [registry]
  • Cabells' Journalytics [registry]
  • CIRC (Integrated Classification of Scientific Journals) [registry]
  • AmeliCA [registry]
  • LILACS (Latin American and Caribbean Health Sciences Literature [registry]
  • EBSCO (Elton Bryson Stephens Company Information Services) [registry]
  • Malena [registry] 
  • Sara Network [registry]
  • SciELO (Scientific Electronic Library Online) [registry]
  • Redalyc (Network of Scientific Journals from Latin America and the Caribbean, Spain and. Portuga) [registry]
 

This journal is licenced under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)