Comparative Performance of Two Multinomial-Based Methods for Obtaining Lower Bounds on the Total Overstatement Error in Accounting Populations
通过模拟研究，比较了三种基于多项式模型的下界估计方法在审计中估计会计总体高估误差下界的表现，评估了不同错误率和随机抽样方法下各方法达到指定置信水平的能力。
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. Coauthors are Robert Plante, Kam-Wah Tsui, and P. Kannan.