3 papers
stat.ME2024
Bridging the Gap Between Design and Analysis: Randomization Inference and Sensitivity Analysis for Matched Observational Studies with Treatment Doses
Jeffrey Zhang, Siyu Heng
Matching is a commonly used causal inference study design in observational studies. Through matching on measured confounders between different treatment groups, valid randomization…
stat.ME2024
Sensitivity Analysis for Matched Observational Studies with Continuous Exposures and Binary Outcomes
Jeffrey Zhang, Dylan Small, Siyu Heng
Matching is one of the most widely used study designs for adjusting for measured confounders in observational studies. However, unmeasured confounding may exist and cannot be remov…
stat.ME2023
Randomization-Based Inference for Average Treatment Effects in Inexactly Matched Observational Studies
Jianan Zhu, Jeffrey Zhang, Zijian Guo +1
Matching is a widely used causal inference design that aims to approximate a randomized experiment using observational data by forming matched sets of treated and control units bas…