Title
Fuzzy Signal Detection Theory: A Monte Carlo Investigation
Abstract
Fuzzy Signal Detection Theory (FSDT) has the potential of enhancing performance measures in detection tasks in which precision of Signal Detection Theory (SDT) analysis is limited by discrete mutually exclusive categorization of the state of the world and/or responses available to the observer. While there have been empirical efforts to demonstrate the benefits and tenability of FSDT, the question still remains whether traditional SDT computational procedures for measures of sensitivity and bias can be used with FSDT procedures. Through the use of Monte Carlo simulation and ROC analysis, the current study examined whether data analyzed by FSDT met the assumptions of traditional SDT on which sensitivity and bias measures are predicated. The results indicated that FSDT does in fact meet the normality and equal variance assumptions of SDT. However, the results also indicated that further theoretical elaboration of 'fuzzy criterion setting' is necessary. Copyright 2011 by Human Factors and Ergonomics Society, Inc. All rights reserved.
Publication Date
11-28-2011
Publication Title
Proceedings of the Human Factors and Ergonomics Society
Number of Pages
1366-1369
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1177/1071181311551284
Copyright Status
Unknown
Socpus ID
81855226068 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/81855226068
STARS Citation
Szalma, James L. and O'Connell, Maureen E., "Fuzzy Signal Detection Theory: A Monte Carlo Investigation" (2011). Scopus Export 2010-2014. 1973.
https://stars.library.ucf.edu/scopus2010/1973