In this paper, we propose a new two-stage unrelated question randomized response technique (RRT) model to estimate the mean of the number of persons possessing a rare sensitive attribute using the Poisson distribution. The utility of proposed two-stage unrelated question RRT model under stratification is also explored. Efficiency comparison between proposed two-stage unrelated question and Singh and Suman (2019 Singh, G. N., and S. Suman. 2019. An ameliorated two-stage randomized response model for estimating a rare stigmatized characteristic using poisson distribution. Kuwait J. Sci 46:21–30.[Web of Science ®] , [Google Scholar]) RRT model is carried out numerically under simple random sampling, and with Suman and Singh (2019 Suman, S., and G. N. Singh. 2019. An ameliorated stratified two-stage randomized response model for estimating the rare sensitive parameter under poisson distribution. Statistics 53 (2):395–416. doi:10.1080/02331888.2019.1569665.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) in stratified random sampling, respectively.

在本文中，我们提出了一种新的两阶段无关问题随机响应技术（RRT）模型，以利用泊松分布估计拥有稀有敏感属性的人数的平均值。还探讨了分层情况下建议的两阶段无关问题RRT模型的实用性。拟议的两阶段无关问题与Singh和Suman（2019年）的效率比较 GN的Singh和S. Suman。2019。一种改进的两阶段随机响应模型，用于使用泊松分布估计罕见的污名化特征。科威特J.科学46：21 - 30。[Web of Science®  ，[Google Scholar]）RRT模型是在简单随机抽样下通过数值进行的，并由Suman和Singh（2019 Suman，S .和GN Singh。2019。一种改进的分层两阶段随机响应模型，用于估计泊松分布下的稀有敏感参数。统计资料53（2）：395 – 416。doi：10.1080 / 02331888.2019.1569665。[Taylor＆Francis Online]，[Web of Science®]  ，[Google Scholar]分别分层分层抽样。