Understanding the diagnostic capabilities of cognitive tests

R. J. Ivnik, G. E. Smith, J. H. Cerhan, B. F. Boeve, E. G. Tangalos, R. C. Petersen

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Statistics (i.e., sensitivity, specificity, hit rates, positive and negative predictive values, odds ratios, and likelihood ratios) that best describe a diagnostic test's ability to classify persons as either "impaired" or "normal," but that are not commonly reported in neuropsychological research, are reviewed. These statistics are applied to Mayo Cognitive Factor Scale scores (MCFS; Smith et al., 1994) to demonstrate information that can be acquired about the diagnostic capabilities of cognitive tests as they are commonly used in clinical settings. Multivariate analyses then generated a statistical model that combines MCFS scores and improves on the diagnostic capabilities of the individual MCFS scores. This model enjoys better diagnostic power than individual scores. It establishes that cognitive testing that uses multiple measures is very good at differentiating normal from impaired cognitive states. Information is also provided that helps clinicians quantify a person's risk for cognitive impairment based on specific cognitive test score(s).

Original languageEnglish (US)
Pages (from-to)114-124
Number of pages11
JournalClinical Neuropsychologist
Volume15
Issue number1
DOIs
StatePublished - Jul 5 2001

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Developmental and Educational Psychology
  • Clinical Psychology
  • Arts and Humanities (miscellaneous)
  • Psychiatry and Mental health

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