Simulation study examines statistical estimators' behavior in auditing multi-location accounting populations, indicating performance differences.
The performance of several statistical estimators in two-stage sampling was examined for accounting populations dispersed over multiple locations. The simulation study involved 64 study populations. The global Stringer bound with cell sampling of dollar units was found to achieve the nominal confidence level in all cases. This bound also tended to be tighter than the mean-per-unit bound with stratified sampling of line items, which statistically achieved the nominal confidence level for only half of the study populations. The global Stringer bound has the disadvantage of frequently leading to rejection of a satisfactory population.
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Hyo et al. (1987) studied this question.
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