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20142026
most citedTime series experiments and causal estimands: exact randomization tests and trading

52 citations · 84 across the 16 of their papers we have counts for

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11 papers · 1 filter

stat.ME2026

Benefits and Costs of Adaptive Sampling

Yu-Shiou Willy Lin, Dae Woong Ham, Iavor Bojinov

Multi-armed bandits are widely used for sequential experimentation in clinical trials, recommendation systems, and online platforms. While regret minimization and valid inference f…

stat.ME2025

Time-Varying Causal Survival Learning

Xiang Meng, Iavor Bojinov

This work bridges the gap between staggered adoption designs and survival analysis to estimate causal effects in settings with time-varying treatments, addressing a fundamental cha…

stat.ME2023★ 2 cited

An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

Biyonka Liang, Iavor Bojinov

Experimentation is crucial for managers to rigorously quantify the value of a change and determine if it leads to a statistically significant improvement over the status quo. As co…

stat.ME2023★ 2 cited

Design-Based Inference for Multi-arm Bandits

Dae Woong Ham, Iavor Bojinov, Michael Lindon +1

Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online d…

stat.ME2022★ 1 cited

Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Panel Experiments

Dae Woong Ham, Iavor Bojinov, Michael Lindon +1

Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. Beyond aiding managerial decision-making, experiments…

stat.ME2022★ 4 cited

Anytime-Valid Linear Models and Regression Adjusted Causal Inference in Randomized Experiments

Michael Lindon, Dae Woong Ham, Martin Tingley +1

Linear models are foundational tools in statistics and ubiquitous across the applied sciences. However, conventional statistical inference -- such as -tests and -tests -- are…

stat.ME2021

Population Interference in Panel Experiments

Kevin Han, Iavor Bojinov, Guillaume Basse

The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in s…

stat.ME2020★ 2 cited

Design and Analysis of Switchback Experiments

Iavor Bojinov, David Simchi-Levi, Jinglong Zhao

Switchback experiments, where a firm sequentially exposes an experimental unit to random treatments, are among the most prevalent designs used in the technology sector, with applic…

stat.ME2020

Panel Experiments and Dynamic Causal Effects: A Finite Population Perspective

Iavor Bojinov, Ashesh Rambachan, Neil Shephard

In panel experiments, we randomly assign units to different interventions, measuring their outcomes, and repeating the procedure in several periods. Using the potential outcomes fr…

stat.ME2020★ 3 cited

A general theory of identification

Guillaume Basse, Iavor Bojinov

What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree on a definition in the context of parametric statistical models --- roughly, a p…

stat.ME2017★ 52 cited

Time series experiments and causal estimands: exact randomization tests and trading

Iavor Bojinov, Neil Shephard

We define causal estimands for experiments on single time series, extending the potential outcome framework to dealing with temporal data. Our approach allows the estimation of som…