Multi-level Adaptive Implementation Strategies (MAISYs): Design Principles, Optimization Questions and Choosing the Right Experimental Design will be presented by Daniel Almirall of the University of Michigan. This event is part of the Dissemination & Implementation Seminar Series, which features leaders in the field to speak on a variety of relevant and timely topics.
- Learn about Multilevel Adaptive Implementation Strategies (MAISYs) and basic MAISY design principles.
- Learn about a variety of novel scientific questions whose answers can be used to construct an optimized MAISY.
- Learn about different types of optimization trial (experimental) designs and how to match the right trial design with the scientific questions of interest
- Begin to understand the difference between the optimization and evaluation of MAISYs.
This seminar will be a hybrid event with opportunities to attend virtually via Zoom webinar or in person in room 4001B on the fourth floor of the Couch Biomedical Research Building.
The Couch building is located on the Washington University Medical Campus. We recommend parking in the Clayton Avenue Garage or taking public transportation.
Get directions to the Couch Biomedical Research Building.
Those attending in person are encouraged to bring their lunch.
About the Speaker
Daniel Almirall (he/his/él)
Co-Director, Data Science for Dynamic Intervention Decision-making Center (d3c)
Department of Statistics, College of Literature, Sciences, and the Arts Survey Research Center Institute for Social Research University of Michigan
Daniel Almirall is a statistician who develops methods to form evidence-based adaptive interventions. Adaptive interventions are used to guide individualized intervention decisions for the on-going management of chronic illnesses or disorders such as drug abuse, depression, anxiety, autism, obesity, or HIV/AIDS. More recently, Mr. Almirall has been developing methods to inform the construction of optimized multilevel adaptive implementation interventions (MAISYs) using Multilevel Implementation SMARTs (MI-SMARTs). He is particularly interested in applications in mental health and substance use.