Authors: Chakraborty B, Murphy S, Strecher V
Title: Inference for non-regular parameters in optimal dynamic treatment regimes.
Journal: Stat Methods Med Res 19(3):317-43
Date: 2010 Jun
Abstract: A dynamic treatment regime is a set of decision rules, one per stage, each taking a patient's treatment and covariate history as input, and outputting a recommended treatment. In the estimation of the optimal dynamic treatment regime from longitudinal data, the treatment effect parameters at any stage prior to the last can be non-regular under certain distributions of the data. This results in biased estimates and invalid confidence intervals for the treatment effect parameters. In this article, we discuss both the problem of non-regularity, and available estimation methods. We provide an extensive simulation study to compare the estimators in terms of their ability to lead to valid confidence intervals under a variety of non-regular scenarios. Analysis of a data set from a smoking cessation trial is provided as an illustration.
Last Updated: 02 Mar 2015