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Comparing treatment policies with assistance from the structural nested mean model
Author(s) -
Lu Xi,
Lynch Kevin G.,
Oslin David W.,
Murphy Susan
Publication year - 2016
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12391
Subject(s) - computer science , nested set model , statistics , econometrics , mathematics , data mining , relational database
Summary Treatment policies, also known as dynamic treatment regimes, are sequences of decision rules that link the observed patient history with treatment recommendations. Multiple, plausible, treatment policies are frequently constructed by researchers using expert opinion, theories, and reviews of the literature. Often these different policies represent competing approaches to managing an illness. Here, we develop an “assisted estimator” that can be used to compare the mean outcome of competing treatment policies. The term “assisted” refers to the fact estimators from the Structural Nested Mean Model, a parametric model for the causal effect of treatment at each time point, are used in the process of estimating the mean outcome. This work is motivated by our work on comparing the mean outcome of two competing treatment policies using data from the ExTENd study in alcohol dependence.