Optimal Dynamic Treatment Methods

Authors

  • Robin Henderson Newcastle University
  • Phil Ansell Newcastle University
  • Deyadeen Alshibani Newcastle University

DOI:

https://doi.org/10.57805/revstat.v9i1.96

Keywords:

anticoagulation, bandit problems, causal inference, diagnostics, regret functions, wild bootstrap

Abstract

This paper reviews and develops methods for implementing in practice recent ideas in the field of optimal dynamic treatment allocation. Given longitudinal sequences of observational data on health status and treatment selection for a cohort of patients, the aim is to determine a regime, or decision rule, which can be used to select treatment in order to optimise some final response or outcome. The approach to this problem that has been taken in the causal inference literature is shown to be extendable to problems in the field of stochastic optimisation. New diagnostic techniques to aid in model assessment are developed, and an application in anticoagulation is presented.

Published

2011-04-07

How to Cite

Henderson , R., Ansell , P., & Alshibani , D. (2011). Optimal Dynamic Treatment Methods. REVSTAT-Statistical Journal, 9(1), 19–36. https://doi.org/10.57805/revstat.v9i1.96