Showing 2024Show all
3 papers · 1 filter
stat.ME2024
Anytime-Valid Inference for Double/Debiased Machine Learning of Causal Parameters
Abhinandan Dalal, Patrick Blöbaum, Shiva Kasiviswanathan +1
Double (debiased) machine learning (DML) has seen widespread use in recent years for learning causal/structural parameters, in part due to its flexibility and adaptability to high-…
stat.ME2024
Planning for gold: Hypothesis screening with split samples for valid powerful testing in matched observational studies
William Bekerman, Abhinandan Dalal, Carlo del Ninno +1
Observational studies are valuable tools for inferring causal effects in the absence of controlled experiments. However, these studies may be biased due to the presence of some rel…
stat.ME2024
PrIsing: Privacy-Preserving Peer Effect Estimation via Ising Model
Abhinav Chakraborty, Anirban Chatterjee, Abhinandan Dalal
The Ising model, originally developed as a spin-glass model for ferromagnetic elements, has gained popularity as a network-based model for capturing dependencies in agents' outputs…