Monotonic single-index models to assess drug interactions.
Although single-index models have been extensively studied, the monotonicity of the link function f in the single-index model is rarely studied. In many situations, it is desirable that f is monotonic, which results in a monotonic single-index model that can be very useful in economics and biometrics. In this article, we propose a monotonic single-index model in which the link function is constructed using penalized I-splines along with constraints on coefficients to achieve monotonicity of the link function f. An algorithm to estimate the single-index parameters and the link function is developed, and the sandwich estimate of the variance of the index parameters is provided. We propose to apply this monotonic single-index model to estimate the dose-response surface and assess drug interactions while considering the variability of the observed data. An extensive simulation study was carried out to evaluate the performance of the proposed monotonic single-index model. A case study is provided to illustrate the application of the proposed model to estimate the dose-response surface and assess drug interactions. Both the simulation and case study show that the proposed monotonic single-index model works very well. Copyright © 2016 John Wiley & Sons, Ltd.
Precision for Medicine, Frederick, MD, U.S.A.
Yubing
Y
Wan
Department of Biostatistics, University of Florida, Gainesville, FL, U.S.A.
Susmita
S
Datta
Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, U.S.A.
J Jack
JJ
Lee
Department of Bioinformatics and Biostatistics, SPHIS, University of Louisville, Louisville, KY, U.S.A.
Maiying
M
Kong
D000465:Algorithms; D004305:Dose-Response Relationship, Drug; D004347:Drug Interactions; D006801:Humans; D015233:Models, Statistical; D013223:Statistics as Topic
I-spline; dose-response surface; drug interaction; single-index model