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;
*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.
TABLE OF CONTENTS
part I|2 pages
Basic Detection Theory and One-Interval Designs
part II|2 pages
Multidimensional Detection Theory and Multi-Interval Discrimination Designs
part III|2 pages
part IV|2 pages