A unified approach to regression analysis under double-sampling designs
A unified approach to regression analysis under double-sampling designs
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DOI：
10.1111/1467-9868.00243
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发表时间：
2000-01-01
影响因子：
5.8
通讯作者：
Chen, YH
中科院分区：
文献类型：
--
作者：
Chen, YH
我们提出了一种在双抽样设计下估计回归参数的统一方法，其中由响应和/或解释变量的粗略或代理测量数据组成的主要样本以及由精确测量数据组成的验证子样本可用。我们假设验证样本是原始样本的简单随机子样本。我们的建议利用特定的参数模型来提取原始样本中包含的部分信息。即使这样的模型指定错误，所得的估计器也是一致的，并且它比仅基于验证数据的估计器实现了更高的渐近效率。讨论具体案例来说明所提出的估计器的应用。
We propose a unified approach to the estimation of regression parameters under double-sampling designs, in which a primary sample consisting of data on the rough or proxy measures for the response and/or explanatory variables as well as a validation subsample consisting of data on the exact measurements are available. We assume that the validation sample is a simple random subsample from the primary sample. Our proposal utilizes a specific parametric model to extract the partial information contained in the primary sample. The resulting estimator is consistent even if such a model is misspecified, and it achieves higher asymptotic efficiency than the estimator based only on the validation data. Specific cases are discussed to illustrate the application of the estimator proposed.