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 supported empirically in many fields. SDT provides superior measures of accuracy and 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.
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1 February 2005
Research Article|
January 01 2005
Analysis of Diagnostic Tasks in Accounting Research Using Signal Detection Theory
Robert J. Ramsay;
Robert J. Ramsay
University of Kentucky.
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Richard M. Tubbs
Richard M. Tubbs
The University of Iowa.
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Online ISSN: 1558-8009
Print ISSN: 1050-4753
American Accounting Association
2005
Behavioral Research in Accounting (2005) 17 (1): 149–173.
Citation
Robert J. Ramsay, Richard M. Tubbs; Analysis of Diagnostic Tasks in Accounting Research Using Signal Detection Theory. Behavioral Research in Accounting 1 February 2005; 17 (1): 149–173. https://doi.org/10.2308/bria.2005.17.1.149
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