Algorithmic and data-driven decisions and recommendations are commonly u...
In a clustered observational study, a treatment is assigned to groups an...
Inverse probability weights are commonly used in epidemiology to estimat...
Research documents that Black patients experience worse general surgery
...
The regression discontinuity (RD) design is widely used for program
eval...
Data-driven decision making plays an important role even in high stakes
...
The idea of covariate balance is at the core of causal inference. Invers...
Gun violence is a critical public safety concern in the United States. I...
Algorithmic recommendations and decisions have become ubiquitous in toda...
Multisite trials, in which treatment is randomized separately in multipl...
Assessing sensitivity to unmeasured confounding is an important step in
...
A pressing challenge in modern survey research is to find calibration we...
To limit the spread of the novel coronavirus, governments across the wor...
In a pilot study during the 2016-17 admissions cycle, the University of
...
Comparing outcomes across hospitals, often to identify underperforming
h...
Staggered adoption of policies by different units at different times cre...
The synthetic control method (SCM) is a popular approach for estimating ...