Detection Theory A User s Guide 2nd Edition by Neil A Macmillan, C Douglas Creelman ISBN 0805842314 9780805842319
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ISBN 10: 0805842314
ISBN 13: 9780805842319
Author: Neil A Macmillan, C Douglas Creelman
Detection Theory is an introduction to one of the most important tools for analysis of data where choices must be made and performance is not perfect. Originally developed for evaluation of electronic detection, detection theory was adopted by psychologists as a way to understand sensory decision making, then embraced by students of human memory. It has since been utilized in areas as diverse as animal behavior and X-ray diagnosis.
This book covers the basic principles of detection theory, with separate initial chapters on measuring detection and evaluating decision criteria. Some other features include:
*complete tools for application, including flowcharts, tables, pointers, and software;
*student-friendly language;
*complete coverage of content area, including both one-dimensional and multidimensional models;
*separate, systematic coverage of sensitivity and response bias measurement;
*integrated treatment of threshold and nonparametric approaches;
*an organized, tutorial level introduction to multidimensional detection theory;
*popular discrimination paradigms presented as applications of multidimensional detection theory; and
*a new chapter on ideal observers and an updated chapter on adaptive threshold measurement.
This up-to-date summary of signal detection theory is both a self-contained reference work for users and a readable text for graduate students and other researchers learning the material either in courses or on their own.
Detection Theory A User s Guide 2nd Table of contents:
Chapter 1: Introduction to Detection Theory
1.1 What is Detection Theory?
1.2 The Historical Context of Detection Theory
1.3 Basic Concepts and Terminology
1.4 The Role of Detection Theory in Science and Engineering
1.5 The Structure of the Book
Chapter 2: Signal Detection Theory Basics
2.1 The Signal Detection Paradigm
2.2 Sensitivity and Bias
2.3 Receiver Operating Characteristic (ROC) Curves
2.4 The Signal Detection Model
2.5 Applications of Signal Detection Theory
Chapter 3: Psychophysics and Signal Detection
3.1 The Psychophysical Approach to Detection
3.2 Thresholds and Just-Noticeable Differences
3.3 Psychometric Functions
3.4 Sensory Sensitivity and Discrimination
3.5 Applications in Human Perception
Chapter 4: Theoretical Foundations of Detection Theory
4.1 Statistical Decision Theory
4.2 Probability Theory and the Likelihood Ratio
4.3 Bayesian Decision Theory
4.4 Minimizing Error Rates
4.5 Optimal Decision Rules
Chapter 5: ROC Curves and Performance Metrics
5.1 Constructing ROC Curves
5.2 Area Under the Curve (AUC)
5.3 Interpretation of ROC Curves
5.4 Comparing Performance Across Different Tests
5.5 Practical Considerations in ROC Analysis
Chapter 6: Detection in Noise
6.1 Types of Noise in Detection Systems
6.2 Signal-to-Noise Ratio (SNR)
6.3 Gaussian Noise and Detection Performance
6.4 The Role of Noise in Real-World Systems
6.5 Noise and Decision-Making
Chapter 7: Decision-Making in Detection Systems
7.1 The Decision Criterion
7.2 The Trade-Off Between Hit Rate and False Alarm Rate
7.3 The Role of the Decision Maker
7.4 Error Types: False Alarms and Misses
7.5 Decision Theory in Real Applications
Chapter 8: Application Areas in Detection Theory
8.1 Signal Detection in Medical Diagnosis
8.2 Applications in Communication Systems
8.3 Detection in Cognitive Psychology
8.4 Applications in Radar and Sonar
8.5 Detection in Image and Speech Processing
Chapter 9: Advanced Topics in Detection Theory
9.1 Multiple Hypothesis Testing
9.2 Adaptive Detection Methods
9.3 Sequential and Bayesian Detection
9.4 Receiver Operating Characteristics in Multidimensional Systems
9.5 Estimation Theory and Detection
Chapter 10: Practical Considerations in Detection Theory
10.1 Designing Detection Systems
10.2 Experimental Design and Data Collection
10.3 Computational Tools for Detection Analysis
10.4 Dealing with Uncertainty in Real-World Systems
10.5 Common Pitfalls in Detection Theory Applications
Chapter 11: Case Studies and Real-World Applications
11.1 Case Study 1: Detection in Radar Systems
11.2 Case Study 2: Medical Imaging and Diagnostics
11.3 Case Study 3: Speech Recognition Systems
11.4 Case Study 4: Environmental Monitoring and Detection
11.5 Summary of Lessons Learned from Case Studies
Chapter 12: Conclusion and Future Directions
12.1 Summary of Key Concepts
12.2 The Future of Detection Theory
12.3 Emerging Technologies and Detection Systems
12.4 Final Thoughts
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