ABSTRACT

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. In these cases, detection theory can transform judgments about subjective experiences, such as perceptions and memories, into quantitative data ready for analysis and modeling.

For beginners, the first three chapters introduce measuring detection and discrimination, evaluating decision criteria, and the utility of receiver operating characteristics. Later chapters cover more advanced research paradigms, including: complete tools for application, including flowcharts, tables, and software; student-friendly language; complete coverage of content area, including both one-dimensional and multidimensional models; integrated treatment of threshold and nonparametric approaches; an organized, tutorial level introduction to multidimensional detection theory; and popular discrimination paradigms presented as applications of multidimensional detection theory.

This modern summary of signal detection theory is both a self-contained reference work for users and a readable text for graduate students and researchers learning the material either in courses or on their own.

part I|136 pages

Basic Detection Theory and One-Interval Designs

chapter 1|24 pages

The Yes-No Experiment

Sensitivity

chapter 2|27 pages

The Yes-No Experiment

Response Bias

chapter 3|31 pages

Beyond Binary Responses

The Rating Experiment and Empirical Receiver Operating Characteristics

chapter 5|28 pages

Threshold Models and Choice Theory

part II|114 pages

Multidimensional Detection Theory and Multi-Interval Discrimination Designs

chapter 6|19 pages

Detection and Discrimination of Compound Stimuli

Tools for Multidimensional Detection Theory

chapter 8|22 pages

Classification Designs

Attention and Interaction

chapter 9|25 pages

Classification Designs for Discrimination

part III|46 pages

Stimulus Factors

chapter 12|17 pages

Components of Sensitivity

part IV|32 pages

Statistics

chapter 13|30 pages

Statistics and Detection Theory