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联合比估计法在敏感性问题调查中的应用

Application of Joint Ratio Estimation Method in Investigation of Sensitive Issues
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摘要 文章基于定性特征敏感性随机化模型——分层抽样下的Warner模型,运用联合比估计法对敏感性问题调查比例的估计量及估计误差进行了理论推导。通过效率比较得出:当各层样本量较大、比估计有效时,联合比估计法的精度优于分层估计法的精度。经调查实例验证,上述结论正确。 Based on the qualitative feature sensitivity randomization model—Warner model under stratified sampling,this paper uses the joint ratio estimation method to theoretically derive the estimators and estimation errors of the survey proportion of sensitive issues.Through efficiency comparison,it is concluded that the precision of the joint ratio estimation method is better than that of the stratified estimation method when the sample size of each layer is large and the ratio estimation is effective.The results of investigation show that the above conclusions are correct.
作者 刘媛媛 冀鹏浩 吴国荣 Liu Yuanyuan;Ji Penghao;Wu Guorong(College of Science,Inner Mongolia Agricultural University,Hohhot 010018,China)
出处 《统计与决策》 北大核心 2024年第8期41-45,共5页 Statistics & Decision
基金 内蒙古自治区高等学校科学研究项目(NJZY22496)。
关键词 分层随机抽样 WARNER模型 联合比估计法 敏感属性比例 stratified random sampling Warner model joint ratio estimation method sensitivity proportion
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