SMART Designs for Developing Adaptive Interventions - Online Course
A 4-Day Livestream Seminar Taught by
Nicholas SeewaldTuesday, July 8 –
Friday, July 11, 2025
10:30am-12:30pm (convert to your local time)
1:30pm-3:00pm
In many settings, such as the treatment of mental health or substance use disorders, oncology, schools, and more, there are outstanding scientific questions about how to tailor treatment to an individual’s changing needs. Adaptive interventions (also called dynamic treatment regimens or adaptive treatment strategies) provide guidelines for whether, how, when, or for whom to change the type, dose, or delivery of treatment. Specifically, adaptive interventions are sequences of decision rules that use ongoing patient information to recommend subsequent treatment, whether that treatment be behavioral, educational, pharmacological, or psychosocial. In schools, personnel might iteratively adapt intervention(s) to address the dynamic needs and contexts of students.
Sequential, multiple-assignment, randomized trials (SMARTs) can be used to construct effective adaptive interventions. The key feature of a SMART is that some or all trial participants are randomized multiple times. This sequential randomization allows researchers to address scientific questions at multiple stages of the development of a high-quality adaptive intervention, such as those about how best to initiate an adaptive intervention, how to define subsets of patients who most benefit from certain adaptations, or how best to adapt treatment for those individuals whose first-line intervention was ineffective. SMARTs can be used to build an evidence base for adaptive treatment of disease, strategies for engagement in treatment, or even implementation interventions to improve adoption of evidence-based practices.
Starting July 8, we are offering this seminar as a 4-day synchronous*, livestream workshop held via the free video-conferencing software Zoom. Each day will consist of two lecture sessions which include hands-on exercises, separated by a 1-hour break. You are encouraged to join the lecture live, but will have the opportunity to view the recorded session later in the day if you are unable to attend at the scheduled time.
*We understand that finding time to participate in livestream courses can be difficult. If you prefer, you may take all or part of the course asynchronously. The video recordings will be made available within 24 hours of each session and will be accessible for four weeks after the seminar, meaning that you will get all of the class content and discussions even if you cannot participate synchronously.
Closed captioning is available for all live and recorded sessions. Captions can be translated to a variety of languages including Spanish, Korean, and Italian. For more information, click here.
More details about the course content
In this 4-day workshop, you will gain detailed knowledge of adaptive interventions and SMARTs, including common design principles and pitfalls, as well as analytic strategies for data from SMARTs. Topics discussed will include common primary, secondary, and exploratory aims in a SMART; power and sample size considerations; primary and secondary data analysis methods; and (time permitting) machine learning approaches to developing more deeply tailored adaptive interventions from SMART data. Throughout, emphasis will be on practical guidance and include case studies and hands-on programming experiences in R.
In this 4-day workshop, you will gain detailed knowledge of adaptive interventions and SMARTs, including common design principles and pitfalls, as well as analytic strategies for data from SMARTs. Topics discussed will include common primary, secondary, and exploratory aims in a SMART; power and sample size considerations; primary and secondary data analysis methods; and (time permitting) machine learning approaches to developing more deeply tailored adaptive interventions from SMART data. Throughout, emphasis will be on practical guidance and include case studies and hands-on programming experiences in R.
Computing
Demonstrations and exercises of sample size calculations and analytic methods will use R/RStudio or RShiny applications. SAS code for a variety of the methods will also be available, but not explicitly used in the course.
If you’d like to take this course but are concerned that you don’t know enough R, there are excellent online resources for learning the basics. Here are our recommendations.
Demonstrations and exercises of sample size calculations and analytic methods will use R/RStudio or RShiny applications. SAS code for a variety of the methods will also be available, but not explicitly used in the course.
If you’d like to take this course but are concerned that you don’t know enough R, there are excellent online resources for learning the basics. Here are our recommendations.
Who should register?
This workshop is for a variety of researchers interested in learning more about tailored, sequential interventions and SMARTs. The workshop is especially geared toward investigators interested in proposing a SMART in their research. Social scientists, clinicians, statisticians, graduate students, and investigators in these fields may be especially interested in the topic. The workshop will be accessible to those with varying levels of quantitative backgrounds. Some prior exposure to clinical trials and regression is helpful but not essential.
This workshop is for a variety of researchers interested in learning more about tailored, sequential interventions and SMARTs. The workshop is especially geared toward investigators interested in proposing a SMART in their research. Social scientists, clinicians, statisticians, graduate students, and investigators in these fields may be especially interested in the topic. The workshop will be accessible to those with varying levels of quantitative backgrounds. Some prior exposure to clinical trials and regression is helpful but not essential.
Seminar outline
Day 1
-
- Introduction to adaptive interventions
- Motivation
- Design principles
- Common scientific questions
- Introduction to SMARTs
- Design principles
- Do I need a SMART?
Day 2
-
- Analyzing data from SMARTs with binary or continuous outcomes
- Main effects
- Comparing adaptive interventions
- Sample size and power
Day 3
-
- Analyzing data from SMARTs with longitudinal or time-to-event outcomes
- Main effects
- Comparing adaptive interventions
- Sample size and power
Day 4
-
- Cluster-randomized SMARTs
- Design principles
- Analytic strategies
- Machine learning methods for building more tailored adaptive interventions
Day 1
-
- Introduction to adaptive interventions
- Motivation
- Design principles
- Common scientific questions
- Introduction to SMARTs
- Design principles
- Do I need a SMART?
- Introduction to adaptive interventions
Day 2
-
- Analyzing data from SMARTs with binary or continuous outcomes
- Main effects
- Comparing adaptive interventions
- Sample size and power
- Analyzing data from SMARTs with binary or continuous outcomes
Day 3
-
- Analyzing data from SMARTs with longitudinal or time-to-event outcomes
- Main effects
- Comparing adaptive interventions
- Sample size and power
- Analyzing data from SMARTs with longitudinal or time-to-event outcomes
Day 4
-
- Cluster-randomized SMARTs
- Design principles
- Analytic strategies
- Machine learning methods for building more tailored adaptive interventions
- Cluster-randomized SMARTs
Payment information
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.
The fee of $995 includes all course materials.
PayPal and all major credit cards are accepted.
Our Tax ID number is 26-4576270.