论文标题
通过匹配评估异质治疗效果估计精度
Assessment of Heterogeneous Treatment Effect Estimation Accuracy via Matching
论文作者
论文摘要
我们研究了异质治疗效果（HTE）估计的准确性的评估，其中HTE无法直接观察到，因此不适用预测误差的标准计算。为了解决难度，我们提出了一种评估方法，通过基于匹配的HTE构建伪观察。我们的贡献是三个方面：首先，我们引入了一个新的匹配距离，这些匹配距离是从随机森林中的接近得分得出的。其次，我们将匹配问题提出为平均最低成本流问题，并提供有效的算法。第三，我们提出了一个与交叉验证评估的匹配原理。我们证明了评估方法对从真实数据集生成的合成数据和数据的功效。
We study the assessment of the accuracy of heterogeneous treatment effect (HTE) estimation, where the HTE is not directly observable so standard computation of prediction errors is not applicable. To tackle the difficulty, we propose an assessment approach by constructing pseudo-observations of the HTE based on matching. Our contributions are three-fold: first, we introduce a novel matching distance derived from proximity scores in random forests; second, we formulate the matching problem as an average minimum-cost flow problem and provide an efficient algorithm; third, we propose a match-then-split principle for the assessment with cross-validation. We demonstrate the efficacy of the assessment approach on synthetic data and data generated from a real dataset.
