Abstract
This paper considers a regression approach to estimating signal detection parameters for rating data. The methodology is based on the statistical modeling of ordinal data and requires only standard statistical software such as SAS (SAS/STAT User’s Guide, 1999) for computation. The approach is more efficient than the current practice of extracting the parameter estimates with the use of specialized software and analyzing the estimates with the use of a standard statisticalpackage. It greatly facilitate s exploration of the effects of covariates on model parameters. The method is illustrated using a published data set from a single factor multiple-alternative perceptual task, and data from a more complex factorial design examining recognition memory rating data.
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This work was supported in part by a paid-leave program from the University Research Council of DePaul University to C.-F. Sheu and partly by a research visitor grant from the University of Newcastle, New South Wales, Australia.
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Sheu, CF., Heathcote, A. A nonlinear regression approach to estimating signal detection models for rating data. Behavior Research Methods, Instruments, & Computers 33, 108–114 (2001). https://doi.org/10.3758/BF03195355
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DOI: https://doi.org/10.3758/BF03195355