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stat.ME2025★ 1 cited
The synthetic instrument: From sparse association to sparse causation
Dingke Tang, Dehan Kong, Linbo Wang
In many observational studies, researchers are often interested in studying the effects of multiple exposures on a single outcome. Standard approaches for high-dimensional data suc…
stat.ME2025
Towards R-learner with Continuous Treatments
Yichi Zhang, Dehan Kong, Shu Yang
The R-learner is widely used in causal inference due to its flexibility and efficiency in estimating the conditional average treatment effect. However, extending the R-learner fram…
stat.ME2024
Fighting Noise with Noise: Causal Inference with Many Candidate Instruments
Xinyi Zhang, Linbo Wang, Stanislav Volgushev +1
Instrumental variable methods provide useful tools for inferring causal effects in the presence of unmeasured confounding. To apply these methods with large-scale data sets, a majo…