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The Theory of Signal Detection (TSD) CHAPTER 5, Psychophysics the Fundamentals
Outline Distributions of Noise and Signal-Noise Likelihood Ratio The Observer’s Criterion ROC Curve Sensitivity Response Bias
Distributions of Noise and Signal-Noise Fundamental to TSD is the concept of noise ,[object Object],♫ Signal detection task
The Likelihood Ratio x may vary on several dimensions (e.g., hue, brightness) x can be located on a single dimension of likelihood ratio
The Observer’s Criterion (β) Observers establish a particular value of l(x) as a criterion Observers operate by a decision rule The setting of the criterion determining which hypothesis about a given piece of information will be accepted and which rejected 	l(x) ≥ β SN l(x) < β N If the observer set a proper criterion, performance will be optimal in a long series of observations
Possible Outcomes
Swets et al. (1961) consider the detection situation to be analogous to a game of chance in which three dice are thrown. Criterion can be influenced by the detection situation, the payoff conditions, and the degree of overlap of the two distributions.
Different strategies of using different criterion The location of optimal criterion is a function of The probabilities of SN and N presentations The costs and values for the various decision outcomes  
β = βopt optimize the winning Observers tend not to set extremely high or extremely low criterion
ROC Curve One of the main sources of evidence supporting TSD comes from the experimental manipulation of variables resulting in data plotted as ROC curves.
As the separation between N and SN increases, the predicted ROC curve rises more rapidly and departs from the positive diagonal of the graph by a greater amount As the criterion is lowered, the predicted point on the ROC curve becomes higher
Test the validity of TSD with ROC curves
Measuring Sensitivity The possible confounding effects of criterion location on threshold estimation
TSD and its associated methodology afford a means of independently measuring the observer’s sensitivity and criterion location. d‘ is a pure index of stimulus detectability that is uncontaminated by the location of the observer’s criterion
An ROC curve is a description of performance changes that are accounted for by a constant d’ and a continuously variable criterion
(p.371)
β is low β is high
Response Bias Response bias is a tendency of the observer, determined by factors other than signal intensity, to favor one response over another Three measures of response bias: β、C、C’
Which index of response bias is better? ,[object Object],β and C’ are statistically dependent of d’ C is statistically independent of d’ The ranges of β and C’ are influenced by d’ 		If d’ ↑, then C’ ↓ and β ↑  		If d’ ↓, then β ↓ and C’ ↑
The three measures of response bias are simply related In some circumstances, the three measures may lead to different conclusions about the experimental results
The End.
               
   

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CHAPTER 5

  • 1. The Theory of Signal Detection (TSD) CHAPTER 5, Psychophysics the Fundamentals
  • 2. Outline Distributions of Noise and Signal-Noise Likelihood Ratio The Observer’s Criterion ROC Curve Sensitivity Response Bias
  • 3.
  • 4. The Likelihood Ratio x may vary on several dimensions (e.g., hue, brightness) x can be located on a single dimension of likelihood ratio
  • 5.
  • 6. The Observer’s Criterion (β) Observers establish a particular value of l(x) as a criterion Observers operate by a decision rule The setting of the criterion determining which hypothesis about a given piece of information will be accepted and which rejected l(x) ≥ β SN l(x) < β N If the observer set a proper criterion, performance will be optimal in a long series of observations
  • 8.
  • 9. Swets et al. (1961) consider the detection situation to be analogous to a game of chance in which three dice are thrown. Criterion can be influenced by the detection situation, the payoff conditions, and the degree of overlap of the two distributions.
  • 10. Different strategies of using different criterion The location of optimal criterion is a function of The probabilities of SN and N presentations The costs and values for the various decision outcomes  
  • 11. β = βopt optimize the winning Observers tend not to set extremely high or extremely low criterion
  • 12. ROC Curve One of the main sources of evidence supporting TSD comes from the experimental manipulation of variables resulting in data plotted as ROC curves.
  • 13. As the separation between N and SN increases, the predicted ROC curve rises more rapidly and departs from the positive diagonal of the graph by a greater amount As the criterion is lowered, the predicted point on the ROC curve becomes higher
  • 14. Test the validity of TSD with ROC curves
  • 15. Measuring Sensitivity The possible confounding effects of criterion location on threshold estimation
  • 16. TSD and its associated methodology afford a means of independently measuring the observer’s sensitivity and criterion location. d‘ is a pure index of stimulus detectability that is uncontaminated by the location of the observer’s criterion
  • 17. An ROC curve is a description of performance changes that are accounted for by a constant d’ and a continuously variable criterion
  • 19. β is low β is high
  • 20. Response Bias Response bias is a tendency of the observer, determined by factors other than signal intensity, to favor one response over another Three measures of response bias: β、C、C’
  • 21.
  • 22.
  • 23. The three measures of response bias are simply related In some circumstances, the three measures may lead to different conclusions about the experimental results
  • 25.                
  • 26.