Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Evaluating time-varying treatment effects in hybrid SMART-MRT designs

Mengbing Li, Inbal Nahum-Shani, Walter Dempsey

TL;DR

These synergistic effects in hybrid SMART-MRTs on both proximal and distal outcomes are formally defined and assessed and practical utility is shown through the analysis of M-Bridge, a hybrid SMART-MRT aimed at reducing binge drinking among first-year college students.

Abstract

Recently a new experimental approach, the hybrid experimental design (HED), was introduced to enable investigators to answer scientific questions about building behavioral interventions in which human-delivered and digital components are integrated and adapted on multiple timescales: slow (e.g., every few weeks) and fast (e.g., every few hours), respectively. An increasingly common HED involves the integration of the sequential, multiple assignment, randomized trial (SMART) with the micro-randomized trial (MRT), allowing investigators to answer scientific questions about potential synergistic effects of digital and human-delivered interventions. Approaches to formalize these questions in terms of causal estimands and associated data analytic methods are limited. In this paper, we formally define and assess these synergistic effects in hybrid SMART-MRTs on both proximal and distal outcomes. Practical utility is shown through the analysis of M-Bridge, a hybrid SMART-MRT aimed at reducing binge drinking among first-year college students.

Evaluating time-varying treatment effects in hybrid SMART-MRT designs

TL;DR

These synergistic effects in hybrid SMART-MRTs on both proximal and distal outcomes are formally defined and assessed and practical utility is shown through the analysis of M-Bridge, a hybrid SMART-MRT aimed at reducing binge drinking among first-year college students.

Abstract

Recently a new experimental approach, the hybrid experimental design (HED), was introduced to enable investigators to answer scientific questions about building behavioral interventions in which human-delivered and digital components are integrated and adapted on multiple timescales: slow (e.g., every few weeks) and fast (e.g., every few hours), respectively. An increasingly common HED involves the integration of the sequential, multiple assignment, randomized trial (SMART) with the micro-randomized trial (MRT), allowing investigators to answer scientific questions about potential synergistic effects of digital and human-delivered interventions. Approaches to formalize these questions in terms of causal estimands and associated data analytic methods are limited. In this paper, we formally define and assess these synergistic effects in hybrid SMART-MRTs on both proximal and distal outcomes. Practical utility is shown through the analysis of M-Bridge, a hybrid SMART-MRT aimed at reducing binge drinking among first-year college students.
Paper Structure (33 sections, 1 theorem, 59 equations, 5 figures, 9 tables)

This paper contains 33 sections, 1 theorem, 59 equations, 5 figures, 9 tables.

Table of Contents

  1. Introduction
  2. The M-Bridge Study and Existing Analyses
  3. Our Contributions
  4. Preliminaries
  5. Study Design and Notation
  6. Potential outcomes and dynamic treatment regimes
  7. Causal Estimands
  8. Estimation and Inference
  9. Modeling Assumptions
  10. Estimation and Inference
  11. Eligibility
  12. Simulation
  13. Simulation Setup and Baseline Methods
  14. Simulation Results
  15. Application to M-Bridge Study
  16. ...and 18 more sections

Key Result

proposition 1

Suppose that the causal assumption assumption:identification and modeling assumptions eq:marginal:model:eq1 hold. Then

Figures (5)

  • Figure 1: A two-stage SMART-MRT hybrid design over $T$ time points. Baseline information is collected time 0. The circled Rs represents randomization events. Upper panel: the restricted SMART component of the hybrid design where only non-responders are re-randomized in Stage 2. Lower panel: the MRT component of the hybrid design that randomizes a binary intervention at each time point.
  • Figure 2: Three commonly used two-stage SMART designs in seewald2020SampleSize. Non-circled Rs and NRs are short for responders and non-responders. Circled Rs represent randomization.
  • Figure : (a) Effect of Early vs Late timing of PNF given fixed bridging strategy.
  • Figure : (a) Effect of Early vs Late timing of PNF given fixed bridging strategy.
  • Figure : (b) Effect of SI vs. PS prompt given fixed initial timing of PNF.

Theorems & Definitions (5)

  • remark 1
  • Example
  • remark 2: Centering
  • remark 3: Weights for Hybrid Designs
  • proposition 1