3 papers
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 methods to target Hypothetical Estimands with longitudinal repeated measures data: Application to the STEP 1 trial
Jack Bowden, Jesper Madsen, Bryan Goldman +3
The STEP 1 randomized trial evaluated the effect of taking semaglutide vs placebo on body weight over a 68 week duration. As with any study evaluating an intervention delivered ove…
stat.ME2023
Just what the doctor ordered: An evaluation of provider preference-based Instrumental Variable methods in observational studies, with application for comparative effectiveness of type 2 diabetes therapy
Laura M. Güdemann, Beverley M. Shields, John M. Dennis +1
Instrumental Variables provide a way of addressing bias due to unmeasured confounding when estimating treatment effects using observational data. As instrument prescription prefere…