Modelling and estimation for optimal treatment decision with interference.

TitleModelling and estimation for optimal treatment decision with interference.
Publication TypeJournal Article
Year of Publication2019
AuthorsSu, Lin, Wenbin Lu, and Rui Song
JournalStat (Int Stat Inst)
Volume8
Issue1
Date Published2019
ISSN2049-1573
Abstract

In many network-based intervention studies, treatment applied on an individual or his or her own characteristics may also affect the outcome of other connected people. We call this interference along network. Approaches for deriving the optimal individualized treatment regimen remain unknown after introducing the effect of interference. In this paper, we propose a novel network-based regression model that is able to account for interaction between outcomes and treatments in a network. Both Q-learning and A-learning methods are derived. We show that the optimal treatment regimen under our model is independent from interference, which makes its application in practice more feasible and appealing. The asymptotic properties of the proposed estimators are established. The performance of the proposed model and methods is illustrated by extensive simulation studies and an application to a mobile game network data.

DOI10.1002/sta4.219
Alternate JournalStat (Int Stat Inst)
Original PublicationModelling and estimation for optimal treatment decision with interference.
PubMed ID31178991
PubMed Central IDPMC6551619
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States