IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v69y2018icp37-49.html
   My bibliography  Save this article

Dedifferentiation and differentiation of intelligence in adults across age and years of education

Author

Listed:
  • Hartung, Johanna
  • Doebler, Philipp
  • Schroeders, Ulrich
  • Wilhelm, Oliver

Abstract

The extent that the structure of cognitive abilities changes across the lifespan or across ability levels is an ongoing debate in intelligence research. The differentiation-dedifferentiation theory states that cognitive abilities differentiate until the beginning of maturity, after which relations increase or dedifferentiate until late adulthood. Spearman's law of diminishing returns proposes that cognitive abilities are more differentiated at higher ability levels. However, the evidence for ability differentiation and age dedifferentiation, in particular, is mixed. A prerequisite for the evaluation of dedifferentiation processes, expressed as changes in ability factor correlations, is the invariance of intelligence across age. However, a strong interpretation of the dedifferentiation hypothesis states that changes in model parameters, such as factor loadings and residual variances, can also be indicative of dedifferentiation. Traditional statistical tools for testing measurement invariance are not feasible for studying parameter changes over a continuous context variable, such as age. However, a recently developed non-parametric method, Local Structural Equation Modeling (LSEM), closes this gap. LSEM is a powerful and versatile method for studying structural changes; it is an improvement over competing methods, because it avoids artificial categorization of a moderator that is continuous in nature and also renounces the determination of a priori parameter functions. Using cross-sectional data from the standardization sample of the Woodcock-Johnson IV Intelligence Test Battery, we present an application and extension of the LSEM approach to accommodate two moderator variables. Specifically, we studied measurement invariance across two context variables, age and years of education, in models testing the unique moderating effect of each, and in a model examining their combined effects. We found no significant moderating effects of age and no effects of years of education on the relation between fluid and crystallized intelligence. Moreover, an interaction of age and years of education with respect to model parameter change cannot be supported.

Suggested Citation

  • Hartung, Johanna & Doebler, Philipp & Schroeders, Ulrich & Wilhelm, Oliver, 2018. "Dedifferentiation and differentiation of intelligence in adults across age and years of education," Intelligence, Elsevier, vol. 69(C), pages 37-49.
    • Handle: RePEc:eee:intell:v:69:y:2018:i:c:p:37-49
    DOI: 10.1016/j.intell.2018.04.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289617301447
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intell.2018.04.003?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. John Schmid & John Leiman, 1957. "The development of hierarchical factor solutions," Psychometrika, Springer;The Psychometric Society, vol. 22(1), pages 53-61, March.
    2. Phillip L. Ackerman, 2000. "Domain-Specific Knowledge as the "Dark Matter" of Adult Intelligence," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 55(2), pages 69-84.
    3. Oberski, Daniel, 2014. "lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i01).
    4. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    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. Savi, Alexander O. & Marsman, Maarten & van der Maas, Han L.J., 2021. "Evolving networks of human intelligence," Intelligence, Elsevier, vol. 88(C).
    2. Steger, Diana & Schroeders, Ulrich & Wilhelm, Oliver, 2019. "On the dimensionality of crystallized intelligence: A smartphone-based assessment," Intelligence, Elsevier, vol. 72(C), pages 76-85.
    3. Demetriou, Andreas & Mougi, Antigoni & Spanoudis, George & Makris, Nicolaos, 2022. "Changing developmental priorities between executive functions, working memory, and reasoning in the formation of g from 6 to 12 years," Intelligence, Elsevier, vol. 90(C).

    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. Pezzuti, Lina & Tommasi, Marco & Saggino, Aristide & Dawe, James & Lauriola, Marco, 2020. "Gender differences and measurement bias in the assessment of adult intelligence: Evidence from the Italian WAIS-IV and WAIS-R standardizations," Intelligence, Elsevier, vol. 79(C).
    2. Reynolds, J.P. & Pilling, M. & Marteau, T.M., 2018. "Communicating quantitative evidence of policy effectiveness and support for the policy: Three experimental studies," Social Science & Medicine, Elsevier, vol. 218(C), pages 1-12.
    3. 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.
    4. Ana Isabel Maldonado & Carol B. Cunradi & Anna María Nápoles, 2020. "Racial/Ethnic Discrimination and Intimate Partner Violence Perpetration in Latino Men: The Mediating Effects of Mental Health," IJERPH, MDPI, vol. 17(21), pages 1-17, November.
    5. Sheppard, Leah D. & O'Reilly, Jane & van Dijke, Marius & Restubog, Simon Lloyd D. & Aquino, Karl, 2020. "The stress-relieving benefits of positively experienced social sexual behavior in the workplace," Organizational Behavior and Human Decision Processes, Elsevier, vol. 156(C), pages 38-52.
    6. Meyers, Maria Christina & van Woerkom, Marianne & Bauwens, Robin, 2023. "Stronger together: A multilevel study of collective strengths use and team performance," Journal of Business Research, Elsevier, vol. 159(C).
    7. Benjamin Motte-Baumvol & Olivier Bonin, 2018. "The spatial dimensions of immobility in France," Transportation, Springer, vol. 45(5), pages 1231-1247, September.
    8. Bence Csaba Farkas & Valérian Chambon & Pierre O. Jacquet, 2022. "Do perceived control and time orientation mediate the effect of early life adversity on reproductive behaviour and health status? Insights from the European Value Study and the European Social Survey," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    9. Wolgast, Anett & Donat, Matthias, 2019. "Cultural mindset and bullying experiences: An eight-year trend study of adolescents' risk behaviors, internalizing problems, talking to friends, and social support," Children and Youth Services Review, Elsevier, vol. 99(C), pages 257-269.
    10. Jorge J. Varela & Cristóbal Hernández & Rafael Miranda & Christopher P. Barlett & Matías E. Rodríguez-Rivas, 2022. "Victims of Cyberbullying: Feeling Loneliness and Depression among Youth and Adult Chileans during the Pandemic," IJERPH, MDPI, vol. 19(10), pages 1-15, May.
    11. Julia Morgan & Casey Canfield, 2021. "Comparing Behavioral Theories to Predict Consumer Interest to Participate in Energy Sharing," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    12. Johannes Bodo Heekerens & Kathrin Heinitz, 2019. "Looking Forward: The Effect of the Best-Possible-Self Intervention on Thriving Through Relative Intrinsic Goal Pursuits," Journal of Happiness Studies, Springer, vol. 20(5), pages 1379-1395, June.
    13. Hayes, Timothy & McArdle, John J., 2017. "Should we impute or should we weight? Examining the performance of two CART-based techniques for addressing missing data in small sample research with nonnormal variables," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 35-52.
    14. David Villarreal-Zegarra & Anthony Copez-Lonzoy & Antonio Bernabé-Ortiz & G J Melendez-Torres & Juan Carlos Bazo-Alvarez, 2019. "Valid group comparisons can be made with the Patient Health Questionnaire (PHQ-9): A measurement invariance study across groups by demographic characteristics," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-15, September.
    15. Gignac, Gilles E. & Kretzschmar, André, 2017. "Evaluating dimensional distinctness with correlated-factor models: Limitations and suggestions," Intelligence, Elsevier, vol. 62(C), pages 138-147.
    16. Martinez, David, 2019. "Immediate and long-term memory and their relation to crystallized and fluid intelligence," Intelligence, Elsevier, vol. 76(C), pages 1-1.
    17. Md. Mominur Rahman & Bilkis Akhter, 2021. "The impact of investment in human capital on bank performance: evidence from Bangladesh," Future Business Journal, Springer, vol. 7(1), pages 1-13, December.
    18. César Merino-Soto & Gina Chávez-Ventura & Verónica López-Fernández & Guillermo M. Chans & Filiberto Toledano-Toledano, 2022. "Learning Self-Regulation Questionnaire (SRQ-L): Psychometric and Measurement Invariance Evidence in Peruvian Undergraduate Students," Sustainability, MDPI, vol. 14(18), pages 1-17, September.
    19. Nathaniel Oliver Iotti & Damiano Menin & Tomas Jungert, 2022. "Early Adolescents’ Motivations to Defend Victims of Cyberbullying," IJERPH, MDPI, vol. 19(14), pages 1-9, July.
    20. Christoph Dworschak, 2024. "Bias mitigation in empirical peace and conflict studies: A short primer on posttreatment variables," Journal of Peace Research, Peace Research Institute Oslo, vol. 61(3), pages 462-476, May.

    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:eee:intell:v:69:y:2018:i:c:p:37-49. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    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.