Literature DB >> 12916655

Are classification accuracy statistics underused in neuropsychological research?

Steven Paul Woods1, Michael Weinborn, David W Lovejoy.   

Abstract

The prevalence of classification accuracy statistics was calculated in five prominent neuropsychology journals and five leading neurology journals for the years 2000 and 2001. Only 29% of neuropsychological articles judged to be appropriate for classification accuracy statistics presented sufficient data to calculate a full range of such analyses. Moreover, classification accuracy statistics were significantly less prevalent in neuropsychology journal articles than in studies published in neurology journals during the same time period. Various indices of sensitivity and/or specificity were present in 31% of neuropsychology articles, whereas fewer than 3% reported predictive values or risk ratios. These findings indicate that classification accuracy statistics, most notably predictive values and risk ratios, are potentially underused in neuropsychology. Investigators and research consumers are encouraged to consider the applicability of classification accuracy statistics as a means of evaluating the clinical relevance of neuropsychological research findings.

Mesh:

Year:  2003        PMID: 12916655     DOI: 10.1076/jcen.25.3.431.13800

Source DB:  PubMed          Journal:  J Clin Exp Neuropsychol        ISSN: 1380-3395            Impact factor:   2.475


  2 in total

1.  Antiretroviral Non-Adherence is Associated With a Retrieval Profile of Deficits in Verbal Episodic Memory.

Authors:  Lisa C Obermeit; Erin E Morgan; Kaitlin B Casaletto; Igor Grant; Steven Paul Woods
Journal:  Clin Neuropsychol       Date:  2015-03-17       Impact factor: 3.535

2.  Assessing cognitive function in cancer patients.

Authors:  Janette Vardy; Karen Wong; Qi-Long Yi; Alison Park; Paul Maruff; Lynne Wagner; Ian F Tannock
Journal:  Support Care Cancer       Date:  2006-03-15       Impact factor: 3.359

  2 in total

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