Analysis of Diagnostic Tasks in Accounting Research Using Signal Detection Theory

Posted: 9 Apr 2005

See all articles by Robert J. Ramsay

Robert J. Ramsay

University of Kentucky - Gatton College of Business and Economics

Richard M. Tubbs

University of Iowa - Department of Accounting

Abstract

Many accounting judgments are diagnostic tasks in which accountants, auditors, managers, or investors discriminate among possible states and decide which one exists. To measure the accuracy of such decisions, most accounting research employs percentage correct, a measure proven to be invalid and unreliable, primarily because it does not control for response bias. This paper describes Signal Detection Theory (SDT), a theoretical model of diagnostic tasks that has been empirically supported in many fields. SDT provides superior accuracy measures and also measures response bias. We discuss the benefits of employing SDT in accounting research and describe an SDT-based reanalysis of data related to two published accounting studies that results in revised conclusions and important additional insights.

Keywords: Diagnostic tasks, Signal Detection Theory, Accuracy, Response bias, Confidence

JEL Classification: M40, M41, M49

Suggested Citation

Ramsay, Robert J. and Tubbs, Richard M., Analysis of Diagnostic Tasks in Accounting Research Using Signal Detection Theory. Available at SSRN: https://ssrn.com/abstract=683113

Robert J. Ramsay

University of Kentucky - Gatton College of Business and Economics ( email )

550 South Limestone
Lexington, KY 40506
United States
859-257-3702 (Phone)
859-257-3654 (Fax)

Richard M. Tubbs (Contact Author)

University of Iowa - Department of Accounting ( email )

108 Pappajohn Business Building
Iowa City, IA 52242-1000
United States
(319) 335-0848 (Phone)
(319) 335-1956 (Fax)

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