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Cancellation Policy: If you cancel your registration at least two weeks before the course is scheduled to begin, you are entitled to a full refund (minus a processing fee of $50).

In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.

A 3-Day Livestream Seminar Taught by Kelley M. Kidwell , Ph.D.

Diseases or disorders such as substance abuse, depression, obesity, ADHD, autism, HIV, diabetes, and cancer require sequences of treatments over time to address changing characteristics of the disease and the patient. Dynamic Treatment Regimens (DTRs) or Adaptive Interventions (AIs) provide guidelines to address the changing needs of disease and the patient. Specifically, AIs are a sequence of decision rules that specify whether, how, for whom, or when to alter the dose, type, or delivery of pharmacological, behavioral, and/or psychosocial treatments.

Effective AIs can be developed and studied in clinical trials called sequential multiple assignment randomized trials (SMARTs). A SMART is a multi-stage trial design that allows for individuals to be randomized at two or more stages based on intermediate outcomes to inform the construction of AIs. The development of AIs from SMARTs is useful for building an evidence base for personalized intervention sequences. SMARTs can also be used to investigate tailored implementation strategies for prevention or uptake of evidence-based practices.

In this workshop, we provide an introduction to dynamic treatment regimens and describe how SMART designs can be used to develop high-quality AIs. Emphasis is on both the design of SMARTs and also on the analysis of SMART data. Discussion around primary, secondary and exploratory aims, power and sample size, and analytic methods will help researchers who are interested in designing a SMART, as well as those who are ready to analyze SMART data. A variety of case studies will be presented to illustrate SMART design and analytic methods throughout the workshop.