Hostname: page-component-77c89778f8-vsgnj Total loading time: 0 Render date: 2024-07-20T02:51:39.890Z Has data issue: false hasContentIssue false
  • English
  • Français

Decomposing age correlations on neuropsychological and cognitive variables

Published online by Cambridge University Press:  01 September 2009

TIMOTHY A. SALTHOUSE
TIMOTHY A. SALTHOUSE*
Affiliation:
Department of Psychology, University of Virginia, Charlottesville, Virginia
*
*Correspondence and reprint requests to: Timothy A. Salthouse, Department of Psychology, University of Virginia, Charlottesville, Virginia 22903. E-mail: salthouse@virginia.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Individual differences associated with age and various neurological conditions are often found in many different neuropsychological and cognitive variables. These variables are frequently treated as though they were independent of one another, with the results interpreted in terms of effects on task-specific processes. However, an alternative perspective evaluates the breadth of the individual difference influences, and takes relations with other variables into account when considering effects on specific neurocognitive variables. This analytical procedure is illustrated in analyses of the WAIS-IV and WMS-IV standardization data, and of data from the Virginia Cognitive Aging Project. (JINS, 2009, 15, 650–661.)

Keywords

CognitionMemoryAgingCorrelation studyStatistical modelsMultivariate analysis
Type
Research Articles
Information
Journal of the International Neuropsychological Society , Volume 15 , Issue 5 , September 2009 , pp. 650 - 661
Copyright
Copyright © The International Neuropsychological Society 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Arbuckle, J.L. (2007). AMOS 16.0. Spring House, PA: Amos Development Corporation.Google Scholar
Becker, J.T., & Salthouse, T.A. (1999). Neuropsychological test performance in the Acquired Immunodeficiency Syndrome: Independent effects of diagnostic group on functioning. Journal of the International Neuropsychological Society, 5, 41–47.CrossRefGoogle Scholar
Carroll, J.B. (1993). Human cognitive abilities. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences. Hillsdale, NJ: Lawrence Erlbaum Publishers.Google Scholar
Craik, F.I.M., & Salthouse, T.A. (Eds.). (2008). Handbook of aging and cognition (3rd ed.). New York: Psychology Press.Google Scholar
Deary, I.J. (2000). Looking down on human intelligence: From psychometrics to the brain. Oxford: Oxford University Press.CrossRefGoogle Scholar
Gustafsson, J.E. (1988). Hierarchical models of individual differences in cognitive abilities. In Sternberg, R.J. (Ed.), Advances in the psychology of human intelligence: Vol. 4. (pp. 35–71). Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Gustafsson, J.E. (2002). Measurement from a hierarchic point of view. In Braun, H.I., Jackson, D.N., & Wiley, D.E. (Eds.), The role of constructs in psychological and educational measurement. (pp. 73–95). Mahwah, NJ: Lawrence Erlbaum Associates.Google Scholar
Jensen, A.R. (1998). The g factor: The science of mental ability. Westport, CT: Prager.Google Scholar
Kline, R.B. (2005). Principles and practice of structural equation modeling. (2nd ed.). New York: Guilford Press.Google Scholar
Salthouse, T.A. (1991). Theoretical perspectives on cognitive aging. Hillsdale, NJ: Lawrence Erlbaum Associates.Google Scholar
Salthouse, T.A. (1998). Independence of age-related influences on cognitive abilities across the life span. Developmental Psychology, 34, 851–864.CrossRefGoogle ScholarPubMed
Salthouse, T.A. (2004). Localizing age-related individual differences in a hierarchical structure. Intelligence, 32, 541–561.CrossRefGoogle Scholar
Salthouse, T.A., & Becker, J.T. (1998). Independent effects of Alzheimer’s disease on neuropsychological functioning. Neuropsychology, 12, 1–11.CrossRefGoogle ScholarPubMed
Salthouse, T.A., & Czaja, S. (2000). Structural constraints on process explanations in cognitive aging. Psychology and Aging, 15, 44–55.CrossRefGoogle ScholarPubMed
Salthouse, T.A., & Davis, H.P. (2006). Organization of cognitive abilities and neuropsychological variables across the lifespan. Developmental Review, 26, 31–54.CrossRefGoogle Scholar
Salthouse, T.A., & Ferrer-Caja, E. (2003). What needs to be explained to account for age-related effects on multiple cognitive variables? Psychology and Aging, 18, 91–110.CrossRefGoogle ScholarPubMed
Salthouse, T.A., Siedlecki, K.L., & Krueger, L.E. (2006). An individual differences analysis of memory control. Journal of Memory and Language, 55, 102–125.CrossRefGoogle ScholarPubMed
Salthouse, T.A., & Tucker-Drob, E.M. (2008). Implications of short-term retest effects for the interpretation of longitudinal change. Neuropsychology, 22, 800–811.CrossRefGoogle ScholarPubMed
Tucker-Drob, E.M. (2009). Global and domain-specific longitudinal changes in cognition throughout adulthood. Unpublished dissertation. University of Virginia.Google Scholar
Wechsler, D. (2008). WAIS-IV: Administration and scoring manual. San Antonio, TX: Pearson.Google Scholar
Wechsler, D. (2009). WMS-IV: Administration and scoring manual. San Antonio, TX: Pearson.Google Scholar
Wechsler, D., Coalson, D.L., & Raiford, S.E. (2008). WAIS-IV: Technical and interpretive manual. San Antonio, TX: Pearson.Google Scholar
Wechsler, D., Holdnack, J.A., & Drozdick, L.W. (2009). WAIS-IV: Technical and interpretive manual. San Antonio, TX: Pearson.Google Scholar