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Activity Number: 111 - Issues and Advances in Power Calculations for Mental Health Studies
Type: Topic Contributed
Date/Time: Monday, July 30, 2018 : 8:30 AM to 10:20 AM
Sponsor: Mental Health Statistics Section
Abstract #329505 Presentation
Title: Sample Size Considerations for Comparing Dynamic Treatment Regimens in a Sequential Multiple-Assignment Randomized Trial with a Continuous Longitudinal Outcome
Author(s): Nicholas J Seewald* and Kelley M Kidwell and James R McKay and Inbal Nahum-Shani and Daniel Almirall
Companies: University of Michigan and University of Michigan and University of Pennsylvania and University of Michigan and University of Michigan
Keywords: Dynamic treatment regimen; Sequential multiple-assignment randomized trial; Clinical trials; Sample size; Power
Abstract:

Clinicians and researchers alike are increasingly interested in how best to individualize interventions. A dynamic treatment regimen (DTR) is a sequence of pre-specified decision rules which guide the delivery of a sequence of treatments that are tailored to the changing needs of the individual. The sequential multiple-assignment randomized trial (SMART) is a research tool that can be used to inform the construction of effective DTRs. We introduce a method for computing sample size for SMARTs in which the primary aim is to compare two embedded DTRs using a continuous repeated-measures outcome collected over the entire study. The sample size method is based on a longitudinal analysis that accounts for unique features of a SMART design. These features include modeling constraints and the over- or under-representation of different sequences of treatment (by design). We illustrate our methods using the ENGAGE study, a SMART aimed at developing a DTR for re-engaging patients with alcohol and cocaine use disorders who have dropped out of treatment.


Authors who are presenting talks have a * after their name.

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