期刊文献+

基于DA插补法的线性回归模型系数估计值的模拟研究 被引量:5

On Estimators of Coefficients of Linear Regression Models Based on Data Augmentation Multiple Imputation
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摘要 Data Augmentation(DA)插补法是最常用的MCMC多重插补法之一。利用模拟方法研究基于DA插补法的线性回归模型的系数估计值,分析估计值的统计性质受无回答机制、无回答率和插补重数的影响。模拟结果显示:在完全随机无回答机制下,选择较小插补重数常常会得到较好的回归系数估计值;在随机无回答机制下,随着无回答率增大而选择更大插补重数往往会得到更好的回归系数估计值;在非随机无回答机制下,选择更大插补重数并不一定总会得到更好的回归系数估计值。 Data Augmentation (DA) multiple imputation is the most commonly used version of the MCMC multiple imputation. This paper simulates coefficients estimators of linear regression model based on the DA multiple imputation and analyzes their statistical properties when non-response mechanism, non-response rate, and number of imputation are given. Simulation results show, it is usually the better coefficients estimators with the small number of imputation at Non-response completely at random mechanism. At non-response at random mechanism, as the non-response rate becomes larger, it is often the better coefficients estimators with the greater number of imputation. At not non-response at random mechanism, the better coefficients estimators is not always follows greater number of imputation.
出处 《统计与信息论坛》 CSSCI 2014年第3期3-8,共6页 Journal of Statistics and Information
基金 国家社会科学基金重大项目<国家统计数据质量管理研究>(09&ZD040) 教育部留学回国人员科研启动基金项目<两阶段设计的若干问题研究>
关键词 DA多重插补法 无回答机制 无回答率 插补重数 data augmentation multiple imputation non-response mechanism non-response rate number of imputation
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参考文献13

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共引文献5

同被引文献40

  • 1Alex Z Fu,唐艳,陈刚.倾向得分法综述[J].中国药物经济学,2008,0(2):27-34. 被引量:15
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