Daniel Almirall, PhD, Associate Professor, Co-Director, Data Science for Dynamic Intervention Decision-making Laboratory (d3lab), Survey Research Center, Institute for Social Research; Department of Statistics, College of Literature Sciences and the Arts, University of Michigan
Bio: Daniel Almirallis Associate Professor in the Institute for Social Research and the Department of Statistics at the University of Michigan. He is a methodologist and statistician who develops methods to form evidence-based adaptive interventions. Adaptive interventions can be used to inform individualized intervention guidelines for the on-going management of chronic illnesses or disorders such as drug abuse, depression, anxiety, autism, obesity, or HIV/AIDS. More recently, Dr. Almirall has been developing methods to form adaptive implementation interventions, to inform how best to tailor sequences of organizational-level strategies to improve the implementation of evidence-based practices. His work includes the development of approaches related to the design, execution, and analysis of sequential multiple assignment randomized trials (SMARTs) which can be used to build adaptive interventions, and of clustered SMARTs to build adaptive implementation interventions. He is particularly interested in applications in child and adolescent mental health research.
Abstract to be posted