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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. 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.
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.
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