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The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: a Meta-Analysis and Meta-Analysis of Individual Participant Data

期刊

NEUROPSYCHOLOGY REVIEW
卷 30, 期 1, 页码 51-96

出版社

SPRINGER
DOI: 10.1007/s11065-019-09423-6

关键词

Factor analysis; Meta-analysis of individual participant data; Meta-analytic SEM; Clinical neuropsychology; Cognitive functioning; Neuropsychological tests; Cattell-horn-Carroll model

资金

  1. Helen Bader Foundation
  2. Northwestern Mutual Foundation
  3. Extendicare Foundation
  4. Clinical and Translational Science Award (CTSA) program through the NIH National Center for Advancing Translational Sciences (NCATS) grant [UL1-TR000427]
  5. National Institute on Aging grant [5R01-AG27161-2]
  6. National Heart, Lung and Blood Institute Contract [N01-HC-25195]
  7. National Institute on Aging [AG16495, AG08122]
  8. National Institute on Neurological Disorders and Stroke [NS17950]
  9. NIH [U01 AG06790, R01 AG08937]
  10. NIA contract [N01 AG12102]
  11. [RF1AG22018]
  12. [R01AG17917]
  13. [P3010161]

向作者/读者索取更多资源

Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.

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