POLYSCORE: A Comparison of Accuracy.

Abstract

Using data collected under a mock crime scenario paradigm, four versions of the John Hopkins University Applied Physics Laboratory (APL) algorithm-based scoring system were evaluated for consistency in scoring accuracy. The four versions were: (a) PASS 2.0, (b) POLYSCORE 2.3, (c) POLYSCORE 2.9, and (d) POLYSCORE 3.0. The algorithm's rates of agreement/disagreement with ground truth were examined, and the same evaluations were made for the psychophysiological detection of deception (PDD) examiners who collected the data. The PDD examiners in this evaluation had an overall accuracy rate of 72.27% when compared to ground truth. The overall rate of accuracy generated by the algorithm (edited dataset) was: (a) PASS 2.0, 63.03%; (b) POLYSCORE 2.3, 67.72%; (c) POLYSCORE 2.9, 72.27%; and (d) POLYSCORE 3.0, 68.91%. With the inconclusive decisions eliminated, the recomputed accuracy rate for the PDD examiners was 79.63%, while each version of the algorithm was comparable (PASS 2.0, 78.95%; POLYSCORE 2.3, 79.21%; POLYSCORE 2.9 83.50%); POLYSCORE 3.0, 82.83%, with both POLYSCORE 2.9 and POLYSCORE 3.0 exceeding the examiners' level of accuracy. In addition to overall accuracy and accuracy based on the test format used, the effects of subjective manipulation of the data were discussed, and information was provided on the occurrence of decision reversals and statistical outliers.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1996
Accession Number
ADA313620

Entities

People

  • N. J. Blackwell

Organizations

  • United States Department of Defense

Tags

Communities of Interest

  • Biomedical
  • Human Systems

DTIC Thesaurus Topics

  • Accuracy
  • Agreements
  • Algorithms
  • Blood Volume
  • Computer Programs
  • Computers
  • Consistency
  • Data Analysis
  • Deception
  • Department Of Defense
  • Detection
  • Money
  • National Security
  • Physics Laboratories
  • Psychophysiology
  • Security
  • Test And Evaluation

Readers

  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Computational Modeling and Simulation