论文标题
连续治疗效果的非参数估计与测量误差
Nonparametric Estimation of the Continuous Treatment Effect with Measurement Error
论文作者
论文摘要
我们通过加权条件期望确定连续估计误差污染的处理的平均剂量反应函数（ADRF）。然后，我们通过最大化局部广义的经验可能性来估算非参数的权重，但要受到纳入反卷积核中的一组条件矩方程的扩展。此后，我们构建了ADRF的反卷积内核估计器。我们得出ADRF估计量的渐近偏置和方差，并提供其渐近线性扩展，这有助于进行统计推断。为了选择我们的平滑参数，我们采用了仿真驱除方法，并提出了一个新的外推过程来稳定计算。蒙特卡洛模拟和真实的数据研究说明了我们方法的实际性能。
We identify the average dose-response function (ADRF) for a continuously valued error-contaminated treatment by a weighted conditional expectation. We then estimate the weights nonparametrically by maximising a local generalised empirical likelihood subject to an expanding set of conditional moment equations incorporated into the deconvolution kernels. Thereafter, we construct a deconvolution kernel estimator of ADRF. We derive the asymptotic bias and variance of our ADRF estimator and provide its asymptotic linear expansion, which helps conduct statistical inference. To select our smoothing parameters, we adopt the simulation-extrapolation method and propose a new extrapolation procedure to stabilise the computation. Monte Carlo simulations and a real data study illustrate our method's practical performance.
