We develop new methodology to improve our understanding of the causal ef...
There is a long-standing debate in the statistical, epidemiological and
...
We propose a doubly robust approach to characterizing treatment effect
h...
Distributed lag models are useful in environmental epidemiology as they ...
We study variation in policing outcomes attributable to differential pol...
The analysis of environmental mixtures is of growing importance in
envir...
Communities often self select into implementing a regulatory policy, and...
There has been increasing interest in recent years in the development of...
We introduce the spike-and-slab group lasso (SSGL) for Bayesian estimati...
We introduce a Bayesian framework for estimating causal effects of binar...
Humans are routinely exposed to mixtures of chemical and other environme...
More advanced visualization tools are needed to assist with the analyses...
Background. Emerging technologies now allow for mass spectrometry based
...
High-throughput metabolomics investigations, when conducted in large hum...