16 citations · 17 across the 6 of their papers we have counts for
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stat.ME2024
Sparse Causal Effect Estimation using Two-Sample Summary Statistics in the Presence of Unmeasured Confounding
Shimeng Huang, Niklas Pfister, Jack Bowden
Observational genome-wide association studies are now widely used for causal inference in genetic epidemiology. To maintain privacy, such data is often only publicly available as s…
stat.ME2024
Instrumental Variable Estimation of Distributional Causal Effects
Lucas Kook, Niklas Pfister
Estimating the causal effect of a treatment on the entire response distribution is an important yet challenging task. For instance, one might be interested in how a pension plan af…
stat.ME2023★ 1 cited
Perturbation-based Effect Measures for Compositional Data
Anton Rask Lundborg, Niklas Pfister
Existing effect measures for compositional features are inadequate for many modern applications, for example, in microbiome research, since they display traits such as high-dimensi…