A Semiparametric Correction for Attenuation
A Semiparametric Correction for Attenuation
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DOI：
10.1080/01621459.1994.10476875
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发表时间：
1994-12
影响因子：
3.7
通讯作者：
J. Sepanski;R. Knickerbocker;R. Carroll
中科院分区：
文献类型：
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作者：
J. Sepanski;R. Knickerbocker;R. Carroll
摘要对协变量有误差测量的广义线性模型提出了一种校正方法。该方法需要一个单独的验证数据集，该数据集由替代变量W和真实协变量X或X的无偏估计值X组成。我们不需要经典的加性测量误差模型，其中代理是无偏的真正的协变量。我们首先得到E（X）的估计|W）的非参数核回归。然后，我们执行标准分析，其中未知X被E（X）的估计所替代|W）。得到了所得回归参数估计量的渐近分布。还讨论了包括X分量的无误差测量的推广。
Abstract A correction method is proposed for models including the generalized linear model when the covariate is measured with error. The method requires a separate validation data set that consists of the surrogate W and the true covariate X or an unbiased estimate X⊃ of X. We do not require the classical additive measurement error model in which the surrogate is unbiased for the true covariates. We first obtain an estimate of E(X|W) by using nonparametric kernel regression of X or X⊃ on W based on the validation data. Then we perform a standard analysis with the unknown X replaced by the estimate of E(X|W). The asymptotic distribution of the resulting regression parameter estimator is obtained. Generalizations to include components of X measured without error are also discussed.