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Article
Exploratory Reconstructability Analysis of Accident TBI Data
International Journal of General Systems
  • Martin Zwick, Portland State University
  • Nancy Ann Carney, Portland State University
  • Rosemary Nettleton, Oregon Health and Science University
Document Type
Post-Print
Publication Date
1-1-2018
Subjects
  • Cybernetics,
  • Reconstructability Analysis,
  • Information Theory,
  • Probabilistic graphical modeling,
  • Multivariate analysis discrete multivariate modeling,
  • Data mining
Abstract

This paper describes the use of reconstructability analysis to perform a secondary study of traumatic brain injury data from automobile accidents. Neutral searches were done and their results displayed with a hypergraph. Directed searches, using both variable-based and state-based models, were applied to predict performance on two cognitive tests and one neurological test. Very simple state-based models gave large uncertainty reductions for all three DVs and sizeable improvements in percent correct for the two cognitive test DVs which were equally sampled. Conditional probability distributions for these models are easily visualized with simple decision trees. Confounding variables and counter-intuitive findings are also reported.

Description

This is the author's version of an article which was published as "Exploratory reconstructability analysis of accident TBI data," in the International Journal of General Systems, (2018). Version of record can be found at https://doi.org/10.1080/03081079.2017.1412435

DOI
10.1080/03081079.2017.1412435
Persistent Identifier
http://archives.pdx.edu/ds/psu/24230
Citation Information
Martin Zwick, Nancy Ann Carney and Rosemary Nettleton. "Exploratory Reconstructability Analysis of Accident TBI Data" International Journal of General Systems Vol. 47 Iss. 2 (2018) p. 174 - 191 ISSN: 1563-5104
Available at: http://works.bepress.com/martin_zwick/80/