1 citations · 2 across the 4 of their papers we have counts for
4 papers
A Universal Framework for Factorial Matched Observational Studies with General Treatment Types: Design, Analysis, and Applications
Jianan Zhu, Tianruo Zhang, Diana Silver +4
Matching is one of the most widely used causal inference frameworks in observational studies. However, all the existing matching-based causal inference methods are designed for eit…
Transporting treatment effects from difference-in-differences studies
Audrey Renson, Ellicott C. Matthay, Kara E. Rudolph
Difference-in-differences (DID) is a popular approach to identify the causal effects of treatments and policies in the presence of unmeasured confounding. DID identifies the sample…
When effects cannot be estimated: redefining estimands to understand the effects of naloxone access laws
Kara E. Rudolph, Catherine Gimbrone, Ellicott C. Matthay +4
Violations of the positivity assumption (also called the common support condition) challenge health policy research, and can result in significant bias, large variance, and invalid…
Powering population health research: Considerations for plausible and actionable effect sizes
Ellicott C. Matthay, Erin Hagan, Laura M. Gottlieb +4
Evidence for Action (E4A), a signature program of the Robert Wood Johnson Foundation, funds investigator-initiated research on the impacts of social programs and policies on popula…