7 papers
Testing the Validity of Instrumental Variable Sets in Causal Additive Models with Non-Constant Effects
Xichen Guo, Feng Xie, Bingbing Tang +5
Instrumental variable (IV) methods are powerful for causal effect estimation with unmeasured confounding, but in practice researchers often face a set of candidate IVs whose validi…
Local Covariate Selection for Average Causal Effect Estimation without Pretreatment and Causal Sufficiency Assumptions
Zeyu Liu, Zheng Li, Feng Xie +3
We study the problem of selecting covariates for unbiased estimation of the total causal effect.Existing approaches typically rely on global causal structure learning over all vari…
Local Learning for Covariate Selection in Nonparametric Causal Effect Estimation with Latent Variables
Zheng Li, Xichen Guo, Feng Xie +3
Estimating causal effects from nonexperimental data is a fundamental problem in many fields of science. A key component of this task is selecting an appropriate set of covariates f…
Testability of Instrumental Variables in Additive Nonlinear, Non-Constant Effects Models
Xichen Guo, Zheng Li, Biwei Huang +3
We address the issue of the testability of instrumental variables derived from observational data. Most existing testable implications are centered on scenarios where the treatment…
Identification and Estimation of the Bi-Directional MR with Some Invalid Instruments
Feng Xie, Zhen Yao, Lin Xie +2
We consider the challenging problem of estimating causal effects from purely observational data in the bi-directional Mendelian randomization (MR), where some invalid instruments,…
Local Causal Structure Learning in the Presence of Latent Variables
Feng Xie, Zheng Li, Peng Wu +3
Discovering causal relationships from observational data, particularly in the presence of latent variables, poses a challenging problem. While current local structure learning meth…
Policy Learning for Balancing Short-Term and Long-Term Rewards
Peng Wu, Ziyu Shen, Feng Xie +3
Empirical researchers and decision-makers spanning various domains frequently seek profound insights into the long-term impacts of interventions. While the significance of long-ter…