Recurrent individual treatment assignment: a treatment policy approach to account for heterogeneous treatment effects.

ABSTRACT: Longitudinal randomized controlled trials generally assign individuals randomly to interventions at baseline and then evaluate how differential average treatment effects evolve over time. This study shows that longitudinal settings could benefit from Recurrent Individual Treatment Assignment (RITA) instead, particularly in the face of (dynamic) heterogeneous treatment effects. Focusing on the optimization of treatment assignment, rather than on estimating treatment effects, acknowledges the presence of unobserved heterogeneous treatment effects and improves overall intervention response when compared to intervention policies in longitudinal settings based on Randomized Controlled Trials (RCTs)-derived average treatment effects. This study develops a RITA-algorithm and evaluates its perform

SUBMITTER: Cornelisz I 

PROVIDER: S-EPMC8817014 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature