Audit Judgment and Evidence Evaluation--A Synopsis of Issues and Research Papers.
综述了1985年南加州大学审计判断研讨会中关于审计证据评价的研究，讨论了贝叶斯推理、非贝叶斯统计、层级推理等模型的优缺点，适合审计研究人员和从业者参考。
Abstract The Editors of the Journal "Auditing: A Journal of Practice & Theory" invited Professor Gary L. Holstrum and Professor Theodore J. Mock to submit this synopsis of the University of Southern California Audit Judgment Symposium in the belief that many audit researchers and professionals who were not able to attend the conference would benefit from the report. A significant area of audit judgment is the evaluation of audit evidence. This synopsis of audit judgment and evidence evaluation research is based upon papers and presentations made at the 1985. The evaluation of audit evidence may be based on one of several models of inference. Audit evidence could be evaluated according to a Bayesian inference model, a non-Bayesian statistical model, a hierarchical or cascaded inference model, a causal reasoning model, or some other form of inference model. Strengths and weaknesses of various inference models were discussed at the Symposium. The Symposium began with presentations of some current behavioral science research on inference models that are expected to be relevant to audit evidence evaluation.