论文标题
基于投影的模型检查是否异质治疗效果
A projection-based model checking for heterogeneous treatment effect
论文作者
论文摘要
在本文中，我们研究了假设检验问题，该问题检查了一部分协变量 /混杂因素是否会显着影响所有协变量的异质治疗效果。在有许多收集的协变量的情况下，该模型检查特别有用，因此我们可以减轻典型的维度诅咒。 在测试构建过程中，我们使用基于投影的想法和基于非参数估算的测试程序来在所有投影方向上构建汇总版本。然后，有趣的是，结果统计量很有趣，而慢速收敛速率没有任何影响，非参数估计通常会受到影响。此功能使该测试的行为就像是全球平滑测试，具有在假设检测中以最快的速度收敛到零类的广泛局部替代方案的能力。此外，该测试可以继承Lobal平滑测试的优点，以使其对振荡替代模型敏感。测试的性能通过数值研究和分析进行了实际数据示例来检查。
In this paper, we investigate the hypothesis testing problem that checks whether part of covariates / confounders significantly affect the heterogeneous treatment effect given all covariates. This model checking is particularly useful in the case where there are many collected covariates such that we can possibly alleviate the typical curse of dimensionality. In the test construction procedure, we use a projection-based idea and a nonparametric estimation-based test procedure to construct an aggregated version over all projection directions. The resulting test statistic is then interestingly with no effect from slow convergence rate the nonparametric estimation usually suffers from. This feature makes the test behave like a global smoothing test to have ability to detect a broad class of local alternatives converging to the null at the fastest possible rate in hypothesis testing. Also, the test can inherit the merit of lobal smoothing tests to be sensitive to oscillating alternative models. The performance of the test is examined by numerical studies and the analysis for a real data example for illustration.
