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Detection Theory: A User's Guide is an introduction to one of the most important tools for the analysis of data where choices must be made, and performance is not perfect.
Detection Theory: A User's Guide is an introduction to one of the most important tools for the analysis of data where choices must be made, and performance is not perfect.
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Autorenporträt
Michael J. Hautus is Head of the Psychophysics Laboratory in the School of Psychology at the University of Auckland, New Zealand. His research interests include quantitative assessment of the functioning of the auditory system, modeling auditory, visual, and flavor judgment, and modeling cognitive processes involved in judgment.
Neil A. Macmillan is a retired Professor of Psychology at Brooklyn College, USA. C. Douglas Creelman, deceased, was a Professor of Psychology at the University of Toronto, Canada. Both of them were privileged to study with founders of detection theory: Creelman with Wilson Tanner and John Swets at the University of Michigan, Macmillan with David Green and Duncan Luce at the University of Pennsylvania.
Inhaltsangabe
PART I. Basic Detection Theory and One-Interval Designs 1. The Yes-No Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond Binary Responses: The Rating Experiment and Empirical Receiver Operating Characteristics 4. Classification Experiments for One-Dimensional Stimulus Sets 5. Threshold Models and Choice Theory PART II. Multidimensional Detection Theory and Multi-Interval Discrimination Designs 6. Detection and Discrimination of Compound Stimuli: Tools for Multidimensional Detection Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8. Classification Designs: Attention and Interaction 9. Classification Designs for Discrimination 10. Identification of Multidimensional Objects and Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive Methods for Estimating Empirical Thresholds 12. Components of Sensitivity PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix 1. Elements of Probability and Statistics Appendix 2. Logarithms and Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software for Detection Theory Appendix 7. Solutions to Selected Problems
PART I. Basic Detection Theory and One-Interval Designs 1. The Yes-No Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond Binary Responses: The Rating Experiment and Empirical Receiver Operating Characteristics 4. Classification Experiments for One-Dimensional Stimulus Sets 5. Threshold Models and Choice Theory PART II. Multidimensional Detection Theory and Multi-Interval Discrimination Designs 6. Detection and Discrimination of Compound Stimuli: Tools for Multidimensional Detection Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8. Classification Designs: Attention and Interaction 9. Classification Designs for Discrimination 10. Identification of Multidimensional Objects and Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive Methods for Estimating Empirical Thresholds 12. Components of Sensitivity PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix 1. Elements of Probability and Statistics Appendix 2. Logarithms and Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software for Detection Theory Appendix 7. Solutions to Selected Problems
PART I. Basic Detection Theory and One-Interval Designs 1. The Yes-No Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond Binary Responses: The Rating Experiment and Empirical Receiver Operating Characteristics 4. Classification Experiments for One-Dimensional Stimulus Sets 5. Threshold Models and Choice Theory PART II. Multidimensional Detection Theory and Multi-Interval Discrimination Designs 6. Detection and Discrimination of Compound Stimuli: Tools for Multidimensional Detection Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8. Classification Designs: Attention and Interaction 9. Classification Designs for Discrimination 10. Identification of Multidimensional Objects and Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive Methods for Estimating Empirical Thresholds 12. Components of Sensitivity PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix 1. Elements of Probability and Statistics Appendix 2. Logarithms and Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software for Detection Theory Appendix 7. Solutions to Selected Problems
PART I. Basic Detection Theory and One-Interval Designs 1. The Yes-No Experiment: Sensitivity 2. The Yes-No Experiment: Response Bias 3. Beyond Binary Responses: The Rating Experiment and Empirical Receiver Operating Characteristics 4. Classification Experiments for One-Dimensional Stimulus Sets 5. Threshold Models and Choice Theory PART II. Multidimensional Detection Theory and Multi-Interval Discrimination Designs 6. Detection and Discrimination of Compound Stimuli: Tools for Multidimensional Detection Theory 7. Comparison (Two-Distribution) Designs for Discrimination 8. Classification Designs: Attention and Interaction 9. Classification Designs for Discrimination 10. Identification of Multidimensional Objects and Multiple Observation Intervals PART III. Stimulus Factors 11. Adaptive Methods for Estimating Empirical Thresholds 12. Components of Sensitivity PART IV. Statistics 13 Statistics and Detection Theory Appendices Appendix 1. Elements of Probability and Statistics Appendix 2. Logarithms and Exponentials Appendix 3. Flowcharts to Sensitivity and Bias Calculations Appendix 4. Some Useful Equations Appendix 5. Tables Appendix 6. Software for Detection Theory Appendix 7. Solutions to Selected Problems
Rezensionen
"The second edition of Detection Theory has been my invaluable companion for many years. It has always been in easy reach to answer my questions. Now that book will move to a place of honored retirement as I call on this new and improved third edition to guide me." -- Jeremy Wolfe, Brigham and Women's Hospital & Harvard Medical School, USA
"The great value of signal detection theory is that it protects you from the dangerous intuitions you will almost certainly otherwise have. After these erroneous intuitions are used to interpret data or build a theory, they will eventually be corrected by someone who knows the difference between d' and beta. It would be better to avoid that fate, and the best way to do that is to carefully study this comprehensive handbook." -- John Wixted, University of California, San Diego, USA
"Signal detection theory was developed in the context of research in sensory psychology, but its impact quickly spread to many other areas, in part because the two previous editions of this book provided such a clear explanation of the theory along with a review of its many applications. This third edition of Detection Theory: A User's Guide has been thoroughly updated and will continue to be an invaluable reference and textbook." -- Walt Jesteadt, Boys Town National Research Hospital, USA
"More than anything else, this book has served as a signpost for my research career. It's that powerful; the tools that general." -- Caren Rotello, University of Massachusetts, Amherst, USA