A global optimisation approach to range-restricted survey calibration.
A global optimisation approach to range-restricted survey calibration.
复制标题
范围限制测量校准的全局优化方法。
DOI：
10.1007/s11222-017-9739-5
复制
发表时间：
2018
影响因子：
2.2
通讯作者：
Espuny-Pujol F
中科院分区：
文献类型：
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作者：
Espuny-Pujol F
调查校准方法修改最低限度的样本权重，以满足域级基准约束（BC），如人口普查总数。这样就可以利用辅助信息来提高抽样数据的代表性（解决覆盖面限制、不答复问题）和基于抽样的总体参数估计数的质量。当样本在某些基准组中计数较小/为零时，或者当施加范围限制（RR）（如阳性）以避免不切实际或极端的权重时，校准方法可能会失败。用户定义的修改BC/RR后，遇到不收敛允许对解决方案的控制很少，和惩罚方法建模不可行性可能无法保证收敛。奇怪的是，这导致在校准高度分类的信息时，即使有，也没有得到充分利用。我们提出了一种始终收敛的灵活的两步全局优化（GO）调查校准方法。评估校准问题的可行性，并允许自动控制BC的最小误差或RR的变化，以保证提前收敛，同时保留校准估计器的良好特性。在不同的情况下，使用各种错误/变化和距离措施的建模替代品制定和讨论。GO方法通过将2012年英格兰健康调查的权重校准为2011年英格兰和威尔士人口普查的精细年龄-性别-区域交叉表（378项）来验证。
Survey calibration methods modify minimally sample weights to satisfy domain-level benchmark constraints (BC), e.g. census totals. This allows exploitation of auxiliary information to improve the representativeness of sample data (addressing coverage limitations, non-response) and the quality of sample-based estimates of population parameters. Calibration methods may fail with samples presenting small/zero counts for some benchmark groups or when range restrictions (RR), such as positivity, are imposed to avoid unrealistic or extreme weights. User-defined modifications of BC/RR performed after encountering non-convergence allow little control on the solution, and penalisation approaches modelling infeasibility may not guarantee convergence. Paradoxically, this has led to underuse in calibration of highly disaggregated information, when available. We present an always-convergent flexible two-step global optimisation (GO) survey calibration approach. The feasibility of the calibration problem is assessed, and automatically controlled minimum errors in BC or changes in RR are allowed to guarantee convergence in advance, while preserving the good properties of calibration estimators. Modelling alternatives under different scenarios using various error/change and distance measures are formulated and discussed. The GO approach is validated by calibrating the weights of the 2012 Health Survey for England to a fine age–gender–region cross-tabulation (378 counts) from the 2011 Census in England and Wales.