Functional additive models for optimizing individualized treatment rules.

ABSTRACT: A novel functional additive model is proposed, which is uniquely modified and constrained to model nonlinear interactions between a treatment indicator and a potentially large number of functional and/or scalar pretreatment covariates. The primary motivation for this approach is to optimize individualized treatment rules based on data from a randomized clinical trial. We generalize functional additive regression models by incorporating treatment-specific components into additive effect components. A structural constraint is imposed on the treatment-specific components in order to provide a class of additive models with main effects and interaction effects that are orthogonal to each other. If primary interest is in the interaction between treatment and the covariates, as is generally the c

SUBMITTER: Park H 

PROVIDER: S-EPMC9043034 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature