Open Access
June 2020 The stratified micro-randomized trial design: Sample size considerations for testing nested causal effects of time-varying treatments
Walter Dempsey, Peng Liao, Santosh Kumar, Susan A. Murphy
Ann. Appl. Stat. 14(2): 661-684 (June 2020). DOI: 10.1214/19-AOAS1293

Abstract

Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and anywhere. Here, we discuss our work on the design of a mobile health smoking cessation intervention study with the goal of assessing whether reminders, delivered at times of stress, result in a reduction/prevention of stress in the near-term and whether this effect changes with time in study. Multiple statistical challenges arose in this effort, leading to the development of the stratified micro-randomized trial design. In these designs each individual is randomized to treatment repeatedly at times determined by predictions of risk. These risk times may be impacted by prior treatment. We describe the statistical challenges and detail how they can be met.

Citation

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Walter Dempsey. Peng Liao. Santosh Kumar. Susan A. Murphy. "The stratified micro-randomized trial design: Sample size considerations for testing nested causal effects of time-varying treatments." Ann. Appl. Stat. 14 (2) 661 - 684, June 2020. https://doi.org/10.1214/19-AOAS1293

Information

Received: 1 June 2018; Revised: 1 May 2019; Published: June 2020
First available in Project Euclid: 29 June 2020

zbMATH: 07239878
MathSciNet: MR4117824
Digital Object Identifier: 10.1214/19-AOAS1293

Keywords: mobile health , nested causal effects , Sequential randomization , stratified micro-randomized trials , weighted-centered least-squares method

Rights: Copyright © 2020 Institute of Mathematical Statistics

Vol.14 • No. 2 • June 2020
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