108 citations · 313 across the 11 of their papers we have counts for
12 papers
Causal Inference with Two Versions of Treatment
Raiden B. Hasegawa, Sameer K. Deshpande, Dylan S. Small +1
Causal effects are commonly defined as comparisons of the potential outcomes under treatment and control, but this definition is threatened by the possibility that the treatment or…
Cross-screening in observational studies that test many hypotheses
Qingyuan Zhao, Dylan S. Small, Paul R. Rosenbaum
We discuss observational studies that test many causal hypotheses, either hypotheses about many outcomes or many treatments. To be credible an observational study that tests many c…
A powerful approach to the study of moderate effect modification in observational studies
Kwonsang Lee, Dylan S. Small, Paul R. Rosenbaum
Effect modification means the magnitude or stability of a treatment effect varies as a function of an observed covariate. Generally, larger and more stable treatment effects are in…
Mortality Rate Estimation and Standardization for Public Reporting: Medicare's Hospital Compare
E. I. George, V. Rockova, P. R. Rosenbaum +2
Bayesian models are increasing fit to large administrative data sets and then used to make individualized recommendations. For instance, Medicare's Hospital Compare webpage provide…
Isolation in the construction of natural experiments
José R. Zubizarreta, Dylan S. Small, Paul R. Rosenbaum
A natural experiment is a type of observational study in which treatment assignment, though not randomized by the investigator, is plausibly close to random. A process that assigns…
Matching for balance, pairing for heterogeneity in an observational study of the effectiveness of for-profit and not-for-profit high schools in Chile
José R. Zubizarreta, Ricardo D. Paredes, Paul R. Rosenbaum
Conventionally, the construction of a pair-matched sample selects treated and control units and pairs them in a single step with a view to balancing observed covariates $\mathbf{x}…