学术沙龙主题: The Poisson Item Count Technique and its non-compliance design for survey with sensitive questions.

报告人: 吴琴，华南师范大学副教授

报告时间: 2025年4月2日(周三)；上午9:00—10:30

报告地点：南校区网络安全大楼 120 会议室

报告人简介：吴琴，博士，毕业于香港浸会大学统计系，现于华南师范大学统计系工作, 副教授。现主持国家自然科学基金面上项目1项（在研），青年项目1项(已结题)，广东省质量工程项目1项(已结题)。相关研究成果被统计杂志Statistical Methods in Medical Research， Statistics in Medicine，Biometrical Journal，Statistical Papers等杂志收录。

报告摘要: The Poisson item count technique (PICT) is a survey method that was recently developed to elicit respondents’ truthful answers to sensitive questions. It simplifies the well-known item count technique (ICT) by replacing a list of independent innocuous questions in known proportions with a single innocuous counting question. However, ICT and PICT both rely on the strong “no design effect assumption” (ie, respondents give the same answers to the innocuous items regardless of the absence or presence of the sensitive item in the list) and “no liar” (ie, all respondents give truthful answers) assumptions. To address the problem of self-protective behavior and provide more reliable analyses, we introduced a noncompliance parameter into the existing PICT. Based on the survey design of PICT, we considered more practical model assumptions and developed the corresponding statistical inferences. Simulation studies were conducted to evaluate the performance of our method. Finally, a real example of automobile insurance fraud was used to demonstrate our method.