5 papers · 1 filter
Mediation Analysis with Multiple Mediators Subject to Missing Not at Random
Yanfei Jin, Shanshan Luo, Xueli Wang +1
Causal mediation analysis serves as a key tool for uncovering the mediating mechanisms linking treatments to outcomes. Existing methods for mediation analysis with multiple mediato…
Identification and multiply robust estimation of causal effects via instrumental variables from an auxiliary population
Wei Li, Jiapeng Liu, Peng Ding +1
Estimating causal effects in a target population with unmeasured confounders is challenging, especially when instrumental variables (IVs) are unavailable. However, IVs from auxilia…
Efficiency-improved doubly robust estimation with non-confounding predictive covariates
Shanshan Luo, Mengchen Shi, Wei Li +2
In observational studies, covariates with substantial missing data are often omitted, despite their strong predictive capabilities. These excluded covariates are generally believed…
Multiply robust estimation of causal effects using linked data
Shanshan Luo, Yechi Zhang, Wei Li
Unmeasured confounding presents a common challenge in observational studies, potentially making standard causal parameters unidentifiable without additional assumptions. Given the…
Modeling High-Dimensional Data with Unknown Cut Points: A Fusion Penalized Logistic Threshold Regression
Yinan Lin, Wen Zhou, Zhi Geng +2
In traditional logistic regression models, the link function is often assumed to be linear and continuous in predictors. Here, we consider a threshold model that all continuous fea…