A single-index model with a surface-link for optimizing individualized dose rules
Abstract
This paper focuses on the problem of modeling and estimating interaction effects between covariates and a continuous treatment variable on an outcome, using a single-index regression approach. The primary motivation is to estimate an optimal individualized dose rule in an observational study. To model possibly nonlinear interaction effects between patients' covariates and a continuous treatment variable, we employ a two-dimensional penalized spline regression on an index-treatment domain, where the index is defined as a linear projection of the covariates. The method is illustrated using two applications as well as simulation experiments. A unique contribution of this work is in the parsimonious (single-index) parametrization specifically defined for the interaction effect term.
Cite
@article{arxiv.2006.00267,
title = {A single-index model with a surface-link for optimizing individualized dose rules},
author = {Hyung Park and Eva Petkova and Thaddeus Tarpey and R. Todd Ogden},
journal= {arXiv preprint arXiv:2006.00267},
year = {2021}
}
Comments
26 pages, 2 figures