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SMART Binary: New Sample Size Planning Resources for SMART Studies with Binary Outcome Measurements.

John J Dziak1, Daniel Almirall2, Walter Dempsey2

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Summary
This summary is machine-generated.

Sequential Multiple-Assignment Randomized Trials (SMARTs) with binary outcomes can improve statistical power using repeated measurements. This study provides new methods for sample size planning in these important behavioral health studies.

Keywords:
Sequential multiple assignment randomized trials (SMARTs)adaptive interventionsbinary outcomepowersample size

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Area of Science:

  • Psychology
  • Behavioral Health Research
  • Clinical Trials

Background:

  • Sequential Multiple-Assignment Randomized Trials (SMARTs) are crucial for tailoring interventions to individual needs in psychological and behavioral health.
  • Existing sample size planning for SMARTs has limitations, particularly for binary outcomes, which often demand larger sample sizes.
  • Current methods for binary outcome SMARTs do not account for the power gains from baseline or repeated outcome measurements.

Purpose of the Study:

  • To address the gap in sample size planning for SMARTs with binary outcomes.
  • To provide simulation procedures and formulas for two-wave repeated measures binary outcomes.
  • To explore power calculations for SMARTs with more than two outcome measurement occasions.

Main Methods:

  • Developed simulation procedures for sample size planning in two-wave repeated measures SMARTs with binary outcomes.
  • Derived approximate formulas for sample size estimation in these designs.
  • Utilized simulations to assess power for studies with multiple outcome measurement occasions.

Main Results:

  • Simulation results demonstrated good agreement with the derived formulas.
  • The study confirmed that incorporating at least one repeated outcome measurement can significantly enhance statistical power under specific conditions.
  • Methods were provided for calculating power in SMARTs with varying numbers of outcome measurement occasions.

Conclusions:

  • Repeated outcome measurements offer a valuable strategy for improving statistical power in Sequential Multiple-Assignment Randomized Trials with binary outcomes.
  • The provided simulation procedures and formulas offer practical tools for researchers planning SMART studies in psychological and behavioral health.
  • These advancements facilitate more efficient and powerful research designs for personalized intervention strategies.