Title: Prevalence profiling: a judgmental context for evaluating initial sample size projections in the audit context

Authors: Edward J. Lusk; Frank Heilig; Michael Halperin

Addresses: School of Business and Economics The State University of New York (SUNY), 101 Broad St Plattsburgh, NY 12901, USA; Leuphana University of Lüneburg, Scharnhorststr, 1D-21335, Lüneburg, Germany; Department of Statistics, The Wharton School, University of Pennsylvania, 3730 Walnut Street, Philadelphia, PA 19104-6340, USA ' Volkswagen Financial Services AG, Gifhornerstr, 57, 38112 Braunschweig, Germany ' Lippincott Library of the Wharton School, University of Pennsylvania, 3506 Walnut St. Philadelphia, PA, 19014, USA

Abstract: The basis of the certification audit, in a non-forensic context is a random sample of sufficient size to create the evidence needed to justify the audit opinion. A key variable in executing this Public Company Accounting Oversight Board (PCAOB) best practices sampling requirement is the prevalence of accounts in error and the related error of and in those accounts. In this paper, we present an integrated sampling approach using the COSO-event (the number of accounts in error) and the substantive valued-event (the error in the accounts) perspectives. We focus on creating pre-sample launch decision-making information by examining the false positive and the false negative error indications over various prevalence error-ranges. We have also developed a decision support system (DSS) that we have introduced as part of our academic consulting to a PCAOB certified public accounting LLP and also have used extensively in the delivery of our auditing and assurance course. This DSS is available free as a download and there are no restrictions on its use.

Keywords: prevalence error ranges; false positives; false negatives; discovery sampling; event sample blending; valued-event sample blending; revalence profiling; initial sample size; sample size projections; auditing; decision support systems; DSS; certified public accounting.

DOI: 10.1504/IJAUDIT.2014.064314

International Journal of Auditing Technology, 2014 Vol.2 No.1, pp.1 - 21

Received: 30 Oct 2013
Accepted: 03 Mar 2014
Published online: 28 Aug 2014 *

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