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Journal of Aging Research
Volume 2014, Article ID 798514, 5 pages
http://dx.doi.org/10.1155/2014/798514
Research Article

A Brief Report on the Factor Structure of the Cognitive Measures in the HRS/AHEAD Studies

1Department of Psychology, Spelman College, 350 Spelman Lane S. W., Box 259, Atlanta, GA 30314, USA
2Department of Psychology, University of Southern California, 711 Seeley G. Mudd Building, Los Angeles, CA 90089, USA

Received 2 December 2013; Revised 7 May 2014; Accepted 7 May 2014; Published 28 May 2014

Academic Editor: F. R. Ferraro

Copyright © 2014 A. Nayena Blankson and John J. McArdle. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. L. Horn and A. N. Blankson, “Foundations for better understanding of cognitive abilities,” in Contemporary Intellectual Assessment: Theories, Tests, and Issues, D. P. Flanagan and P. L. Harrison, Eds., The Guilford Press, New York, NY, USA, 3rd edition, 2012. View at Google Scholar
  2. J. J. McArdle, G. G. Fisher, and K. M. Kadlec, “Latent variable analyses of age trends of cognition in the health and retirement Study, 1992–2004,” Psychology and Aging, vol. 22, no. 3, pp. 525–545, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. K. Suthers, J. K. Kim, and E. Crimmins, “Life expectancy with cognitive impairment in the older population of the United States,” Journals of Gerontology B: Psychological Sciences and Social Sciences, vol. 58, no. 3, pp. S179–S186, 2003. View at Google Scholar · View at Scopus
  4. S. Y. Moody-Ayers, K. M. Mehta, K. Lindquist, L. Sands, and K. E. Covinsky, “Black-white disparities in functional decline in older persons: the role of cognitive function,” Journals of Gerontology A: Biological Sciences and Medical Sciences, vol. 60, no. 7, pp. 933–939, 2005. View at Google Scholar · View at Scopus
  5. C. Spearman, “General intelligence: objectively determined and measured,” The American Journal of Psychology, vol. 15, pp. 201–292, 1904. View at Google Scholar
  6. R. B. Cattell, “Some theoretical issues in adult intelligence testing,” Psychological Bulletin, vol. 38, article 592, 1941. View at Google Scholar
  7. D. T. Lykken, “Statistical significance in psychological research,” Psychological Bulletin, vol. 70, no. 3, pp. 151–159, 1968. View at Publisher · View at Google Scholar · View at Scopus
  8. S. G. Heeringa and J. H. Connor, Technical Description of the Health and Retirement Study Sample Design, Institute for Social Research Pub. DR-002, University of Michigan, Ann Arbor, Mich, USA, 1996.
  9. C. Leacock, Ed., Getting Started with the Health and Retirement Study, Version 1. 0, Survey Research Center, Institute of Social Research, University of Michigan, Ann Arbor, Mich, USA, 2006.
  10. M. B. Ofstedal, G. G. Fisher, and A. R. Herzog, “Documentation of cognitive functioning measures in the Health and Retirement Study,” HRS/AHEAD Documentation Report DR-006, University of Michigan, Ann Arbor, Mich, USA, 2005. View at Google Scholar
  11. J. Brandt, M. Spencer, and M. Folstein, “The telephone interview for cognitive status,” Neuropsychiatry, Neuropsychology and Behavioral Neurology, vol. 1, no. 2, pp. 111–117, 1988. View at Google Scholar · View at Scopus
  12. M. F. Folstein, S. E. Folstein, and P. R. McHugh, “Mini-Mental State: a practical method for grading the cognitive state of patients for the clinician,” Journal of Psychiatric Research, vol. 12, pp. 189–198, 1975. View at Google Scholar
  13. G. G. Fisher, H. Hassan, W. L. Rodgers, and D. R. Weir, Health and Retirement Study Imputation of Cognitive Functioning Measures: 1992–2010 Early Release, University of Michigan, Ann Arbor, Mich, USA, 2012.
  14. A. Beauducel and P. Y. Herzberg, “On the performance of maximum likelihood versus means and variance adjusted weighted least squares estimation in CFA,” Structural Equation Modeling, vol. 13, no. 2, pp. 186–203, 2006. View at Publisher · View at Google Scholar · View at Scopus
  15. L. K. Muthén and B. O. Muthén, Mplus User's Guide, Muthén & Muthén, Los Angeles, Calif, USA, 1998–2012.
  16. M. A. Browne and R. Cudeck, “Alternative ways of assessing model fit,” in Testing Structural Equation Models, K. A. Bollen and J. S. Long, Eds., Chapter 6, pp. 136–162, Sage, Newbury Park, Calif, USA, 1993. View at Google Scholar
  17. J. H. Steiger and J. C. Lind, “Statistically-based tests for the number of common factors,” in Proceedings of the Annual Spring Meeting of the Psychometric Society, Iowa City, Iowa, USA, 1980.
  18. P. M. Bentler, “Comparative fit indexes in structural models,” Psychological Bulletin, vol. 107, no. 2, pp. 238–246, 1990. View at Google Scholar · View at Scopus
  19. L.-T. Hu and P. M. Bentler, “Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives,” Structural Equation Modeling, vol. 6, no. 1, pp. 1–55, 1999. View at Publisher · View at Google Scholar · View at Scopus
  20. R. J. Van Lieshout, K. Cleverley, J. M. Jenkins, and K. Georgiades, “Assessing the measurement invariance of the Center for Epidemiologic Studies Depression Scale across immigrant and non-immigrant women in the postpartum period,” Archives of Women's Mental Health, vol. 14, no. 5, pp. 413–423, 2011. View at Publisher · View at Google Scholar · View at Scopus