Valliant Richard, Hubbard Frost, Lee Sunghee, Chang Chiungwen
Institute for Social Research, University of Michigan.
J Surv Stat Methodol. 2014 Jun;2(2):182-209. doi: 10.1093/jssam/smu006.
Sampling households using commercial lists has the potential to reduce costs and to efficiently identify some subgroups for which target sample sizes are desired. However, the information on the lists for demographics like age is usually incomplete and inaccurate. We demonstrate that this inexact information can still be used to improve the efficiency with which some, but not all, demographic subgroups can be located during sampling. The paper also illustrates the use of nonlinear programming as a means for finding sample allocations that are subject to a variety of practical constraints. A commercial address list and data from the National Survey of Family Growth and the Health and Retirement Study are used to illustrate the calculation of allocations to strata of housing units defined by information on the list.
使用商业列表对家庭进行抽样有可能降低成本，并有效地识别出一些需要达到目标样本量的子群体。然而，像年龄这样的人口统计学列表信息通常是不完整和不准确的。我们证明，这种不准确的信息仍可用于提高抽样过程中定位部分（而非全部）人口统计学子群体的效率。本文还阐述了使用非线性规划作为一种手段来寻找受各种实际约束的样本分配方式。使用一份商业地址列表以及来自全国家庭成长调查和健康与退休研究的数据来说明根据列表信息定义的住房单元层的分配计算。
