LEARNING OBJECTIVES
- to understand what an interrupted time series analysis (ITS) is;
- identify when it is appropriate;
- list advantages/disadvantages;
- interpret results in a specific example
PRESENTER(S)
Elizabeth Juarez-Colunga, PhD, is an Assistant Professorin the Colorado School of Public Health. She received her BS in Applied Mathematics and MSc in Statistics in Mexico, and her doctoral degree in Statistics from Simon Fraser University in Canada. Elizabeth’s areas of expertise and interest include: (i) analysis of data with dependencies at different levels including longitudinal and clustered data, which builds upon generalized linear and nonlinear mixed models, (ii) analysis of repeated events data such as pulmonary exacerbations, which evolve as extension of survival analysis methods, (iii) joint modeling of multiple outcomes, and (iv) analysis of observational data. She has been involved in the design and analysis of several health outcomes research studies, including for instance, the The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) project, a pragmatic trial to assist weight loss in a low-income population, and several observational studies in surgical outcomes.
Angela Moss, MS received a Bachelor in Engineering Degree from Vanderbilt University. After working as a Chemical Engineer in both the Biotechnology and Aerospace fields she earned a Master's Degree from University of Colorado in Biostatistics. She has been working as an analyst at ACCORDS since 2014.
