Sponsor
This work was supported by the U.S. Army Contracting Command. Aberdeen Proving Ground, Natick Contracting Division, under grant W911QY-14-C-0086.
Published In
International Journal of General Systems
Document Type
Post-Print
Publication Date
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.
DOI
10.1080/03081079.2017.1412435
Persistent Identifier
http://archives.pdx.edu/ds/psu/24230
Citation Details
Zwick, Martin; Carney, Nancy Ann; and Nettleton, Rosemary, "Exploratory Reconstructability Analysis of Accident TBI Data" (2018). Systems Science Faculty Publications and Presentations. 108.
http://archives.pdx.edu/ds/psu/24230
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