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