52 citations · 84 across the 16 of their papers we have counts for
17 papers
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…
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…
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…
Balancing Risk and Reward: An Automated Phased Release Strategy
Yufan Li, Jialiang Mao, Iavor Bojinov
Phased releases are a common strategy in the technology industry for gradually releasing new products or updates through a sequence of A/B tests in which the number of treated unit…
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…
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…
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…
Quantifying the Value of Iterative Experimentation
Jialiang Mao, Iavor Bojinov
Over the past decade, most technology companies and a growing number of conventional firms have adopted online experimentation (or A/B testing) into their product development proce…
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…
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…
Estimating the effectiveness of permanent price reductions for competing products using multivariate Bayesian structural time series models
Fiammetta Menchetti, Iavor Bojinov
The Florence branch of an Italian supermarket chain recently implemented a strategy that permanently lowered the price of numerous store brands in several product categories. To qu…
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…
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…
Causal inference from observational data: Estimating the effect of contributions on visitation frequency atLinkedIn
Iavor Bojinov, Ye Tu, Min Liu +1
Randomized experiments (A/B testings) have become the standard way for web-facing companies to guide innovation, evaluate new products, and prioritize ideas. There are times, howev…
Diagnosing missing always at random in multivariate data
Iavor Bojinov, Natesh Pillai, Donald Rubin
Models for analyzing multivariate data sets with missing values require strong, often unassessable, assumptions. The most common of these is that the mechanism that created the mis…
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…
Multiple Imputation Using Gaussian Copulas
Florian M. Hollenbach, Iavor Bojinov, Shahryar Minhas +3
Missing observations are pervasive throughout empirical research, especially in the social sciences. Despite multiple approaches to dealing adequately with missing data, many schol…