Print Email Facebook Twitter A flexible micro-randomized trial design and sample size considerations Title A flexible micro-randomized trial design and sample size considerations Author Xu, Jing (Duke-NUS Medical School) Yan, Xiaoxi (Duke-NUS Medical School) Figueroa, C.A. (TU Delft Information and Communication Technology; University of California) Williams, Joseph Jay (University of Toronto) Chakraborty, Bibhas (Duke-NUS Medical School; National University of Singapore) Date 2023 Abstract Technological advancements have made it possible to deliver mobile health interventions to individuals. A novel framework that has emerged from such advancements is the just-in-time adaptive intervention, which aims to suggest the right support to the individuals when their needs arise. The micro-randomized trial design has been proposed recently to test the proximal effects of the components of these just-in-time adaptive interventions. However, the extant micro-randomized trial framework only considers components with a fixed number of categories added at the beginning of the study. We propose a more flexible micro-randomized trial design which allows addition of more categories to the components during the study. Note that the number and timing of the categories added during the study need to be fixed initially. The proposed design is motivated by collaboration on the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation study, which learns to deliver effective text messages to encourage physical activity among patients with diabetes and depression. We developed a new test statistic and the corresponding sample size calculator for the flexible micro-randomized trial using an approach similar to the generalized estimating equation for longitudinal data. Simulation studies were conducted to evaluate the sample size calculators and an R shiny application for the calculators was developed. Subject generalized estimating equationjust-in-time adaptive interventionlongitudinaldatamHealthmicro-randomized trial To reference this document use: http://resolver.tudelft.nl/uuid:6afad265-baf4-4e96-ac5b-4bfe5faac737 DOI https://doi.org/10.1177/09622802231188513 ISSN 0962-2802 Source Statistical Methods in Medical Research, 32 (9), 1766-1783 Part of collection Institutional Repository Document type journal article Rights © 2023 Jing Xu, Xiaoxi Yan, C.A. Figueroa, Joseph Jay Williams, Bibhas Chakraborty Files PDF xu_et_al_2023_a_flexible_ ... ations.pdf 826.93 KB Close viewer /islandora/object/uuid:6afad265-baf4-4e96-ac5b-4bfe5faac737/datastream/OBJ/view