Parametric and Semiparametric Model‐Based Estimates of the Finite Population Mean for Two‐Stage Cluster Samples with Item Nonresponse
Parametric and Semiparametric Model‐Based Estimates of the Finite Population Mean for Two‐Stage Cluster Samples with Item Nonresponse
复制标题
基于参数和半参数模型的项目无响应两阶段聚类样本的有限总体均值估计
DOI：
10.1111/j.1541-0420.2007.00816.x
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发表时间：
2007
期刊：
影响因子：
1.9
通讯作者：
R. Little
中科院分区：
文献类型：
--
作者：
Ying Yuan;R. Little
摘要本文涉及两阶段整群样本的项目无反应调整。具体地说，我们关注两种类型的不可忽略的无响应：依赖于协变量和潜在的集群特征的无响应，以及依赖于协变量和缺失结果的无响应。在这种情况下，标准权重和分摊调整容易产生偏见。为了获得一致的估计，我们通过对这两种类型的缺失数据机制建模来扩展标准的随机效应模型。我们还提出了基于在倾向得分上拟合样条的半参数方法，以削弱关于结果与协变量之间关系的假设。通过仿真将这些新方法与已有方法进行了比较。使用国家健康和营养检查调查数据来说明这些方法。
Summary This article concerns item nonresponse adjustment for two‐stage cluster samples. Specifically, we focus on two types of nonignorable nonresponse: nonresponse depending on covariates and underlying cluster characteristics, and depending on covariates and the missing outcome. In these circumstances, standard weighting and imputation adjustments are liable to be biased. To obtain consistent estimates, we extend the standard random‐effects model by modeling these two types of missing data mechanism. We also propose semiparametric approaches based on fitting a spline on the propensity score, to weaken assumptions about the relationship between the outcome and covariates. These new methods are compared with existing approaches by simulation. The National Health and Nutrition Examination Survey data are used to illustrate these approaches.