IDEAS home Printed from https://ideas.repec.org/a/spr/psycho/v64y1999i2p113-128.html
   My bibliography  Save this article

On the relationship between the higher-order factor model and the hierarchical factor model

Author

Listed:
  • Yiu-Fai Yung
  • David Thissen
  • Lori McLeod

Abstract

No abstract is available for this item.

Suggested Citation

  • Yiu-Fai Yung & David Thissen & Lori McLeod, 1999. "On the relationship between the higher-order factor model and the hierarchical factor model," Psychometrika, Springer;The Psychometric Society, vol. 64(2), pages 113-128, June.
    • Handle: RePEc:spr:psycho:v:64:y:1999:i:2:p:113-128
    DOI: 10.1007/BF02294531
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/BF02294531
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/BF02294531?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Karl Holzinger & Frances Swineford, 1937. "The Bi-factor method," Psychometrika, Springer;The Psychometric Society, vol. 2(1), pages 41-54, March.
    2. Ledyard Tucker, 1940. "The role of correlated factors in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 5(2), pages 141-152, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abhijit Guha & Timna Bressgott & Dhruv Grewal & Dominik Mahr & Martin Wetzels & Elisa Schweiger, 2023. "How artificiality and intelligence affect voice assistant evaluations," Journal of the Academy of Marketing Science, Springer, vol. 51(4), pages 843-866, July.
    2. Li Cai, 2015. "Lord–Wingersky Algorithm Version 2.0 for Hierarchical Item Factor Models with Applications in Test Scoring, Scale Alignment, and Model Fit Testing," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 535-559, June.
    3. Fu, Zhihui & Zhang, Xue & Tao, Jian, 2020. "Gibbs sampling using the data augmentation scheme for higher-order item response models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    4. MacPherson, Sarah E. & Allerhand, Michael & Cox, Simon R. & Deary, Ian J., 2019. "Individual differences in cognitive processes underlying Trail Making Test-B performance in old age: The Lothian Birth Cohort 1936," Intelligence, Elsevier, vol. 75(C), pages 23-32.
    5. repec:jss:jstsof:34:i03 is not listed on IDEAS
    6. Carlo Cavicchia & Maurizio Vichi & Giorgia Zaccaria, 2020. "The ultrametric correlation matrix for modelling hierarchical latent concepts," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(4), pages 837-853, December.
    7. Minjeong Jeon & Frank Rijmen & Sophia Rabe-Hesketh, 2018. "CFA Models with a General Factor and Multiple Sets of Secondary Factors," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 785-808, December.
    8. Li Cai, 2010. "A Two-Tier Full-Information Item Factor Analysis Model with Applications," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 581-612, December.
    9. Sonnier, Garrett P. & Rutz, Oliver J. & Ward, Adrian F., 2023. "Estimating the effect of brand beliefs on brand evaluations when beliefs are measured with error," International Journal of Research in Marketing, Elsevier, vol. 40(3), pages 552-569.
    10. Frank Rijmen & Minjeong Jeon & Matthias von Davier & Sophia Rabe-Hesketh, 2014. "A Third-Order Item Response Theory Model for Modeling the Effects of Domains and Subdomains in Large-Scale Educational Assessment Surveys," Journal of Educational and Behavioral Statistics, , vol. 39(4), pages 235-256, August.
    11. Satomi Doi & Masaya Ito & Yoshitake Takebayashi & Kumiko Muramatsu & Masaru Horikoshi, 2018. "Factorial validity and invariance of the Patient Health Questionnaire (PHQ)-9 among clinical and non-clinical populations," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-9, July.
    12. Carlo Cavicchia & Maurizio Vichi, 2022. "Second-Order Disjoint Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 289-309, March.
    13. Wai, Jonathan & Lakin, Joni M. & Kell, Harrison J., 2022. "Specific cognitive aptitudes and gifted samples," Intelligence, Elsevier, vol. 92(C).
    14. Robert Jennrich & Peter Bentler, 2011. "Exploratory Bi-Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 76(4), pages 537-549, October.
    15. Sayed H. Kadhem & Aristidis K. Nikoloulopoulos, 2023. "Bi-factor and Second-Order Copula Models for Item Response Data," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 132-157, March.
    16. Leigh McAlister & Garrett Sonnier & Tom Shively, 2012. "The relationship between online chatter and firm value," Marketing Letters, Springer, vol. 23(1), pages 1-12, March.
    17. Carlo Cavicchia & Maurizio Vichi & Giorgia Zaccaria, 2023. "Hierarchical disjoint principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(3), pages 537-574, September.
    18. Kano, Yutaka & Takai, Keiji, 2011. "Analysis of NMAR missing data without specifying missing-data mechanisms in a linear latent variate model," Journal of Multivariate Analysis, Elsevier, vol. 102(9), pages 1241-1255, October.
    19. Niels G. Waller, 2018. "Direct Schmid–Leiman Transformations and Rank-Deficient Loadings Matrices," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 858-870, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Niels G. Waller, 2018. "Direct Schmid–Leiman Transformations and Rank-Deficient Loadings Matrices," Psychometrika, Springer;The Psychometric Society, vol. 83(4), pages 858-870, December.
    2. Harry Harman, 1941. "On the rectilinear prediction of oblique factors," Psychometrika, Springer;The Psychometric Society, vol. 6(1), pages 29-35, February.
    3. Victoria T. Tanaka & George Engelhard & Matthew P. Rabbitt, 2020. "Using a Bifactor Model to Measure Food Insecurity in Households with Children," Journal of Family and Economic Issues, Springer, vol. 41(3), pages 492-504, September.
    4. Michael Edwards, 2010. "A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 75(3), pages 474-497, September.
    5. Kan, Kees-Jan & van der Maas, Han L.J. & Levine, Stephen Z., 2019. "Extending psychometric network analysis: Empirical evidence against g in favor of mutualism?," Intelligence, Elsevier, vol. 73(C), pages 52-62.
    6. Terrance Savitsky & Daniel McCaffrey, 2014. "Bayesian Hierarchical Multivariate Formulation with Factor Analysis for Nested Ordinal Data," Psychometrika, Springer;The Psychometric Society, vol. 79(2), pages 275-302, April.
    7. Daniel Segall, 2001. "General ability measurement: An application of multidimensional item response theory," Psychometrika, Springer;The Psychometric Society, vol. 66(1), pages 79-97, March.
    8. Ando, Tomohiro, 2009. "Bayesian factor analysis with fat-tailed factors and its exact marginal likelihood," Journal of Multivariate Analysis, Elsevier, vol. 100(8), pages 1717-1726, September.
    9. Minjeong Jeon & Frank Rijmen & Sophia Rabe-Hesketh, 2013. "Modeling Differential Item Functioning Using a Generalization of the Multiple-Group Bifactor Model," Journal of Educational and Behavioral Statistics, , vol. 38(1), pages 32-60, February.
    10. Robert Jennrich & Peter Bentler, 2012. "Exploratory Bi-factor Analysis: The Oblique Case," Psychometrika, Springer;The Psychometric Society, vol. 77(3), pages 442-454, July.
    11. Li Cai, 2015. "Lord–Wingersky Algorithm Version 2.0 for Hierarchical Item Factor Models with Applications in Test Scoring, Scale Alignment, and Model Fit Testing," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 535-559, June.
    12. Elena A. Erosheva & S. McKay Curtis, 2017. "Dealing with Reflection Invariance in Bayesian Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 82(2), pages 295-307, June.
    13. Hua, Lei & Joe, Harry, 2017. "Multivariate dependence modeling based on comonotonic factors," Journal of Multivariate Analysis, Elsevier, vol. 155(C), pages 317-333.
    14. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2016. "Fast ML Estimation of Dynamic Bifactor Models: An Application to European Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 215-282, Emerald Group Publishing Limited.
    15. Katherine Stroebe & Tom Postmes & Susanne Täuber & Alwin Stegeman & Melissa-Sue John, 2015. "Belief in a Just What? Demystifying Just World Beliefs by Distinguishing Sources of Justice," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-30, March.
    16. Jiaxi Zhang & Meng Cui & Wei Wang & Huijie Lu & Qing Wu & Xia Zhu & Danmin Miao & Yan Zhang & Xi Feng & Wei Xiao, 2014. "The Coexistence of Coping Resources and Specific Coping Styles in Stress: Evidence from Full Information Item Bifactor Analysis," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-11, May.
    17. Richard Zinbarg & William Revelle & Iftah Yovel & Wen Li, 2005. "Cronbach’s α, Revelle’s β, and Mcdonald’s ω H : their relations with each other and two alternative conceptualizations of reliability," Psychometrika, Springer;The Psychometric Society, vol. 70(1), pages 123-133, March.
    18. Nana Kim & Daniel M. Bolt & James Wollack, 2022. "Noncompensatory MIRT For Passage-Based Tests," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 992-1009, September.
    19. Rockstuhl, Thomas & Van Dyne, Linn, 2018. "A bi-factor theory of the four-factor model of cultural intelligence: Meta-analysis and theoretical extensions," Organizational Behavior and Human Decision Processes, Elsevier, vol. 148(C), pages 124-144.
    20. Carlo Cavicchia & Maurizio Vichi & Giorgia Zaccaria, 2020. "The ultrametric correlation matrix for modelling hierarchical latent concepts," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(4), pages 837-853, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:psycho:v:64:y:1999:i:2:p:113-128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.