We study causal inference and efficient estimation for the expected numb...
In healthcare, there is much interest in estimating policies, or mapping...
Existing statistical methods can be used to estimate a policy, or a mapp...
In the standard difference-in-differences research design, the parallel
...
Constructing an optimal adaptive treatment strategy becomes complex when...
Existing literature on constructing optimal regimes often focuses on
int...
Researchers are often interested in learning not only the effect of
trea...
Existing methods in estimating the mean outcome under a given dynamic
tr...
Unmeasured confounding is a key threat to reliable causal inference base...
One of the main goals of sequential, multiple assignment, randomized tri...
Inverse probability weighted estimators are the oldest and potentially m...
The cyclical and heterogeneous nature of many substance use disorders
hi...
Q-learning is a regression-based approach that is widely used to formali...
Sequential, multiple assignment, randomized trial (SMART) designs have b...