My current primary interest is in causal inference and multi-stage decisions sometimes called dynamic treatment regimes or adaptive treatment strategies. Dynamic treatment regimes are individually tailored treatments; formally a dynamic treatment regime is a sequence of decision rules that specify when to alter the therapy and specify which intensity or type of subsequent therapy should be offered. The decision rules employ variables such as patient response, risk, burden, adherence, and preference, collected during prior therapy. In a dynamic regime, the decision rules are specified prior to the beginning of the initial therapy. These regimes hold the promise of maximizing treatment efficacy by avoiding ill effects due to over-treatment and by providing increased treatment levels to those who can benefit. Once developed, the decision rules can be used to augment/enhance the clinical judgment used in practice.
I am particularly interested in developing statistical methods and experimental designs that can be used in
formulating dynamic treatment regimes. This work is funded by
National Institute on Drug Abuse and by
National Institute of Mental Health.
I work with researchers at
The Methodology Center on these topics.
