Comparative Performance of Two Muitinomial-Based Methods for Obtaining Lower Bounds on the Total Overstatement Error in Accounting Populations
Bibliographic Data
| ID | 19417748 |
|---|---|
| Authors | Ella Mae Matsumura (0000-0002-4647-1225, University of Wisconsin–Madison), Robert Plante (Purdue University West Lafayette), Kam-Wah Tsui, Kam‐Wah Tsui (University of Wisconsin–Madison), P K Kannan (0000-0003-0738-0766, University of Arizona), P Kannan (0009-0001-8892-6371) |
| Year | 1991 |
| Volume | 9 |
| Issue | 4 |
| Pages | 423-429 |
| Publication date | 1991-10-01 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.1991.10509869 |
| OpenAlex | W2019926706 |
| Language | EN |
| References cited | 5 |
Accurately estimating a lower bound on the total overstatement error in an accounting population is important in many audit decision situations. This article reports the results of a simulation study of three lower-bound estimation procedures based on a multinomial model with a dollar-unit sampling scheme. The ability of each procedure to attain a specified confidence level is assessed with respect to changes in error rate and random sampling method. The simulation study shows that the tested procedures perform well in achieving specified lower-bound coverages on the total overstatement error in the chosen accounting populations
Confidence interval · Econometrics · Economics · Multinomial distribution · Population · Statistics · Upper and lower bounds · Advanced Statistical Methods and Models · Advanced Statistical Process Monitoring · Auditing, Earnings Management, Governance · Computer Science · Mathematics · Accounting
| Highly cited | No |
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