We develop a class of regression-based estimators, called Principal Components Difference-in-Differences (PCDID) estimators, for treatment effect estimation. Analogous to a control function approach,

Taylor & Francis Group2022-06-14 更新70

Replication Data for: Causal Inference with Interference and Noncompliance in Two-Stage Randomized Experiments.

因果推断

随机实验

In many social science experiments, subjects often interact with each other and as a result one unit's treatment influences the outcome of another unit. Over the last decade, a significant progress ha

DataONE2020-06-16 更新100

Local Gaussian process extrapolation for BART models with applications to causal inference

回归模型

因果推断

Bayesian additive regression trees (BART) is a semi-parametric regression model offering state-of-the-art performance on out-of-sample prediction. Despite this success, standard implementations of BAR

DataCite Commons2023-07-26 更新90