多层次结构数据的BOOTSTRAP方法研究  

Bootstrap Methodological Study of Hierarchical Data

作　　者：任仕泉[1] 陈峰[2] 杨树勤[3] 

机构地区：[1]四川大学工商管理学院服务管理研究所 [2]南通医学院医学统计教研室 [3]四川大学华西公共卫生学院

出　　处：《统计研究》2002年第3期55-59,共5页Statistical Research

摘　　要：When the statistics distribution of interested is complex or vague, Bootstrap method may be used to estimate standard error and confidence interval. However, the results derived from parametric and nonparametric Bootstrap methods applied to hierarchically structured data may be different. According to the comparing, we found and concluded that nonparametric Bootstrap method is relating seldom affected by the distribution in models. In terms of the nonparametric Bootstrap sampling, the effectiveness of sampling on the highest level unit is more satisfactory than lower level units. The estimation of confidence intervals and hypothesis testing of intraclass corelation coefficients is discussed based on multilevel generalized linear models.When the statistics distribution of interested is complex or vague, Bootstrap method may be used to estimate standard error and confidence interval. However, the results derived from parametric and nonparametric Bootstrap methods applied to hierarchically structured data may be different. According to the comparing, we found and concluded that nonparametric Bootstrap method is relating seldom affected by the distribution in models. In terms of the nonparametric Bootstrap sampling, the effectiveness of sampling on the highest level unit is more satisfactory than lower level units. The estimation of confidence intervals and hypothesis testing of intraclass corelation coefficients is discussed based on multilevel generalized linear models.

关 键 词：多层次结构数据 多水平统计模型 BOOTSTRAP方法 

分 类 号：C811[社会学—统计学]