4 papers
Best for which estimand? A known-truth benchmark of longitudinal-matching and target-trial-emulation methods for time-varying treatments
M. Ehsan Karim
On a non-collapsible survival mechanism, longitudinal-matching and target-trial-emulation methods are not competing estimators of one truth but answers to different causal question…
Cluster on the Subject, Not the Record: Confidence Intervals and Simultaneous Bands for Additive-Hazards Sequential Trial Emulation
M. Ehsan Karim
Sequential trial emulation (STE) estimates the effect of a sustained treatment by stacking nested emulated trials with inverse-probability weighting. Additive-hazards STE estimator…
Cross-Fitted Survey-Weighted TMLE with Design-Based Variance for Causal Machine Learning
M. Ehsan Karim
Cross-fitting is not a refinement of survey-weighted causal machine learning but, once the nuisances are flexible, what restores valid inference. We study the population average tr…
When Does Trial-Real-World Data Fusion Improve Precision? Model Auditing and Selection-Aware Inference for Adaptive-TMLE
M. Ehsan Karim
Augmenting a randomized controlled trial (RCT) with real-world data (RWD) promises greater efficiency, but how much a given fusion delivers, and how to attach honest uncertainty to…