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stat.ME2026

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…

stat.ME2024

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…

stat.ME2024

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,…

stat.ME2024

Causal Inference with Outcomes Truncated by Death and Missing Not at Random

Wei Li, Yuan Liu, Shanshan Luo +1

In clinical trials, principal stratification analysis is commonly employed to address the issue of truncation by death, where a subject dies before the outcome can be measured. How…

stat.ME2024

Assessing the causes of continuous effects by posterior effects of causes

Shanshan Luo, Yixuan Yu, Chunchen Liu +2

To evaluate a single cause of a binary effect, Dawid et al. (2014) defined the probability of causation, while Pearl (2015) defined the probabilities of necessity and sufficiency.…