7 papers
Debiased inference for proximal dose-response function
Daeyoung Ham, Sihan Wu, Yifan Cui
In this paper, we study nonparametric inference for the causal dose-response curve of a continuous-treatment under unmeasured confounding by leveraging treatment- and outcome-induc…
A General Framework for Optimal Group Sequential Testing via Mixed-Integer Linear Programming
Dae Woong Ham, Stefanus Jasin, Xuejun Zhao
Sequential hypothesis tests are widely adopted as a principled way to perform multiple tests on data that arrives over time. In particular, researchers frequently utilize group seq…
Bias-Variance Tradeoff of Matching Prior to Difference-in-Differences When Parallel Trends is Violated
Mingxuan Ge, Dae Woong Ham
Quasi-experimental causal inference methods have become central in empirical operations management for guiding managerial decisions. Among these, empiricists utilize the Difference…
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…
Sparse Multivariate Linear Regression with Strongly Associated Response Variables
Daeyoung Ham, Bradley S. Price, Adam J. Rothman
We propose new methods for multivariate linear regression when the regression coefficient matrix is sparse and the error covariance matrix is dense. We assume that the error covari…
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…