Graubard B I, Korn E L
Biometry Branch, National Cancer Institute, Bethesda, MD 20892, USA.
Stat Methods Med Res. 1996 Sep;5(3):263-81. doi: 10.1177/096228029600500304.
Health surveys typically have stratified multistage clustered designs in which individuals are sampled with differing probabilities. The sampling design is taken into account in a classical survey analysis by using sample-weighted estimators and variance estimators calculated at the primary-sampling-unit level. In this paper we investigate the possibility of modelling the sampling design using fixed and random effects to redefine target parameters, improve estimators of standard target parameters and improve standard variance estimators. References in which this type of additional modelling was used in health surveys are given. The problem of estimating population variance components is discussed in some detail, with an application involving estimation of between- and within-family variance components in the Hispanic Health and Nutrition Examination Survey.
健康调查通常采用分层多阶段整群设计，其中个体以不同概率被抽样。在经典的调查分析中，通过使用样本加权估计量和在初级抽样单元层面计算的方差估计量来考虑抽样设计。在本文中，我们研究了使用固定效应和随机效应来对抽样设计进行建模的可能性，以便重新定义目标参数、改进标准目标参数的估计量以及改进标准方差估计量。文中给出了在健康调查中使用此类额外建模的参考文献。我们较为详细地讨论了估计总体方差分量的问题，并给出了一个应用实例，该实例涉及在西班牙裔健康与营养检查调查中估计家庭间和家庭内方差分量。
