On Combining Evidence from Sub-Populations into a Composite Conclusion

In audit testing scenarios, the question arises as to the appropriate way to combine or aggregate the evidence gathered from separate tests of sub-populations into an overall conclusion about the amount of audit risk being borne - that is, the risk of a material amount of misstatement remaining undetected in the overall population at the conclusion of such separate audit tests. The Poisson distribution-based "max rule," a method of combining judgments of audit risk based on tests of sub-populations, is examined. Although the max rule may be justified at the planning stages of the audit, it is shown that if it is used at the evaluation stage of the audit, it can lead to underestimation of the upper error limit and overall risk faced upon completing tests of sub-populations. As a result, it should not be used to evaluate results of audit procedures applied to sub-populations to draw overall audit conclusions