Small area estimation in presence of nonresponse
Small area estimation in presence of nonresponse
复制标题
无响应时的小面积估计
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
E. Rocco
中科院分区：
文献类型：
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作者：
C. Giusti;E. Rocco
在标准调查估计中，无响应问题是众所周知的，存在各种方法来调整这一现象。不太清楚的是无响应对小面积估计的影响。本文提出了一种概率加权估计方法，该方法考虑了在单位水平上采用小面积模型时信息不响应机制对小面积平均预测器的影响。我们遵循Pfefferman等人（1998）提出的方法，以补偿多层模型中不平等样本选择概率的影响。由于调查抽样者无法控制响应机制，我们的情况进一步复杂化，因为响应概率是未知的，需要估计。为了分析所建议的加权估计过程的性能，我们给出了在不同场景下实施的几个蒙特卡罗实验的结果。这些结果表明，如果响应概率“适当”估计，那么所提出的程序是有效的，最重要的是，如果在调查中同时存在无响应和小面积估计问题，则需要同时解决。
In standard survey estimation the problem of nonresponse is well known and a variety of methods exist to adjust for this phenomenon. Less well understood are the effects of nonresponse on small area estimation. In this paper we propose a probability weighted estimation procedure that adjusts for the effect of an informative nonresponse mechanism on the small area mean predictor when a small area model at unit level is adopted. We follow the approach suggested by Pfefferman et al. (1998) to compensate for the effect of unequal sample selection probabilities in multilevel models. Since the survey sampler has no control over the response mechanism, our situation is further complicated by the fact that the response probabilities are unknown and need to be estimated. To analyse the performance of the suggested weighted estimation procedure we present the results of several Monte Carlo experiments implemented under different scenarios. These results show that the proposed procedure is effective if the response probabilities are “properly” estimated and, above all, that the nonresponse and small area estimation problems, if both present in a survey, need to be addressed simultaneously.