Integrating Statistical and Non-Statistical Audit Evidence in Attribute Sampling Using Belief Functions
نویسندگان
چکیده
The main purpose of this article is to show how one can integrate statistical evidence from attribute sampling with non-statistical evidence within the Dempster-Shafer belief function framework. In particular, the article shows: (1) how to determine the sample size in attribute sampling to obtain a desired level of belief that the true attribute occurrence rate of the population lies in a given interval; (2) what level of belief is obtained for a specified interval given the sample result; and (3) how to integrate non-statistical evidence with the statistical evidence arising from the attribute sampling. These issues are important to the auditor and therefore we use auditing examples to illustrate the process. As intuitively expected, we find that the sample size increases as the desired level of belief in the interval increases. In evaluating the sample results, we again find results that are intuitively appealing. For example, provided the sample occurrence rate falls in the interval B for a given number of occurrences of the attribute, we find that the belief in B, Bel(B), increases as the sample size increases. However, if the sample occurrence rate falls outside of the interval then Bel(B) is zero. Note that, in general, both Bel(B) and Bel(notB) are zero when the sample occurrence rate falls at the end points of the interval. These results extend similar results already available for variables sampling. However, the auditor faces an additional problem for attribute sampling: how to convert belief in an interval for control exceptions into belief in an interval for material misstatements in the financial statements, so that it can be combined with evidence from other sources in implementations of the Audit Risk Model. We discuss this problem, and investigate conversion methods that are consistent with current auditing practice.
منابع مشابه
Audit Decisions Using Belief Functions: A Review
This article provides an overview of the audit process along with the belief-function approach to audit decisions. In particular, the article highlights the advantages of using belief functions for representing uncertainties in the audit evidence and discusses the audit risk model of the American Institute of Certified Public Accountants as a plausibility model. Also, the article discusses the ...
متن کاملIntegrating statistical and nonstatistical audit evidence using belief functions: A case of variable sampling
The main purpose of this article is to show how one can integrate statistical and nonstatistical items of evidence under the belief function framework. First, we use the properties of consonant belief functions to define the belief that the true mean of a variable lies in a given interval when a statistical test is performed for the variable. Second, we use the above definition to determine the...
متن کاملWhy We Should Consider Belief Functions in Auditing Research and Practice
The Auditor's Report, Vol. 28, No. 2, March 2005 Why We Should Consider Belief Functions in Auditing Research and Practice Rajendra P. Srivastava, University of Kansas, and Theodore J. Mock, University of Southern California and Maastricht University Recent events in the auditing profession [sometimes called the ‘accounting’ profession] have clearly called for a reconsideration of the paradigms...
متن کاملStatistical Sampling Revisited
Auditing standards are undergoing revision in the wake of recent, massive audit failures. Legislative and regulatory bodies are focusing more critically on auditors than ever before. Yet, contemplated revisions to auditing standards leave untouched ambiguities and unresolved issues that have reduced the effectiveness of the authoritative literature for decades. One of the longest-standing issue...
متن کامل