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Mathematical Social Sciences 23 (1992) 175-197 North-Holland
 

Summary: Mathematical Social Sciences 23 (1992) 175-197
North-Holland
175
Comparing the biased choice model
and multidimensional decision
bound models of identification
F. Gregory Ashby, W. William Lee and J.D. Balakrishnan
Department of Psychology, University of California ai Santa Barbara, Santa Barbara, CA 93106, USA
Communicated by A.A. J. Marley
Received 10 August 1990
Revised 27 June 1991
The biased choice model (BCM) of Lute (1963) and general recognition theory (CRT) of Ashby and
Townsend (1986) are compared with respect to their ability to account for data from identification ex-
periments. Specifically, by using CRT we investigate the ability of the BCM to account for data
characterized by violations of perceptual independence and perceptual and decisional separability, and
by homoscedasticity of the perceptual distributions. The effects of varying the dimensionality of the
perceptual space are also studied. It is shown that the BCM has extreme difficulty accounting for data
from experiments in which: (1) the stimuli are constructed from two physical components; (2) the percep-
tual means are positioned unevenly in the perceptual space; and (3) different stimuli are characterized
by different amounts of perceptual variability or perceptual dependence. In general, however, the BCM

  

Source: Ashby, F. Gregory - Department of Psychology, University of California at Santa Barbara

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences