From the 1 of 9 linked papers with an AI index.
9 papers
Selecting among Missingness Models for Sequential Outcomes with Nonignorable Nonresponse
Yingying Wang, Yuan Liu, Shanshan Luo
Sequential outcomes in longitudinal studies and multi-wave surveys may be missing not at random at both earlier and later occasions. We study graphical models in which at least one…
Mediation Analysis with Multiple Mediators Subject to Missing Not at Random
Yanfei Jin, Shanshan Luo, Xueli Wang +1
The paper develops methods to identify and estimate causal mediation effects when multiple mediators have missing values that are not missing at random, providing theory, simulatio…
Apportioning Causal Responsibility of Two Risk Factors for an Adverse Outcome via Counterfactual Attribution
Shanshan Luo, Yafang Deng, Qingyuan Zhao +1
Unlike traditional causal inference, which prospectively evaluates the effects of causes, apportioning causal responsibility requires a retrospective assessment to deduce the cause…
Identifying Causal Effects Using Instrumental Variables from the Auxiliary Dataset
Kang Shuai, Shanshan Luo, Wei Li +1
Instrumental variable approaches have gained popularity for estimating causal effects in the presence of unmeasured confounders. However, the availability of instrumental variables…
Identifiability of causal effects with non-Gaussianity and auxiliary covariates
Kang Shuai, Shanshan Luo, Yue Zhang +2
Assessing causal effects in the presence of unmeasured confounding is challenging. Although auxiliary variables, such as instrumental variables, are commonly used to identify causa…
Assessing Interactive Causes of an Occurred Outcome Due to Two Binary Exposures
Shanshan Luo, Wei Li, Xueli Wang +2
In contrast to evaluating treatment effects, causal attribution analysis focuses on identifying the key factors responsible for an observed outcome. For two binary exposure variabl…