Intensive Longitudinal Methods Workshop
Analysis of Intensive Longitudinal Data: Experience Sampling and Ecological Momentary Assessment
June 13-17, 2022
Capacity: 50 participants
Applications for the Analysis of Intensive Longitudinal Data: Experience Sampling and Ecological Momentary Assessment workshop include an abbreviated curriculum vitae (no more than five pages), a description of why you would like to attend the workshop (no more than 300 words) and a description of how you plan to use the knowledge gained in the future (no more than 300 words). Applications are carefully reviewed using a variety of criteria, as outlined below.
- Preparedness for the course. A curriculum vitae and Personal Statements are reviewed to ascertain whether the applicant is academically prepared for the course.
- Opportunity to use training in future research. Personal statements are reviewed to determine whether applicants will have a strong likelihood to use this training in future research. The applicants' affiliated institutions are also assessed for availability of necessary equipment and resources required to utilize the training in future research.
- Comprehensiveness of Personal Statements. The Personal Statements are also reviewed for clear and comprehensive answers describing the applicants' reasons for applying to the course and goals for using training in future research and teaching. Personal Statements that are incomplete or unclear cannot be fairly evaluated.
Analysis of Intensive Longitudinal Data: Experience Sampling and Ecological Momentary Assessment workshop will be held remotely. Lectures and programming/lab sessions will be recorded and made available at the start of the workshop. Each lecture will cover the conceptual foundation of the statistical models and be accompanied by a programming/lab session that covers the implementation of the statistical models in R, an open-source comprehensive statistical program. In addition, for each lecture and associated programming/lab session, the instructors will host an interactive Q&A session via zoom at 12 p.m. and 4 p.m. ET each day. Participants are encouraged to watch the lectures and programming/lab sessions prior to the live Q&A and be ready with questions. Participants are also encouraged to apply the models to their data and bring questions about the implementation of the models to their own data to the Q&A sessions.
About the Workshop
The Analysis of Intensive Longitudinal Data workshop will be hosted by the Cornell Center for Integrative Developmental Science. This workshop highlights the range of approaches used in the analysis of data from experience sampling, ecological momentary assessment, daily diary, and other intensive longitudinal paradigms. The training is intended for faculty, postdoctoral fellows, and advanced graduate students in the behavioral and social sciences who are already familiar with these kinds of data and with basic multilevel modeling (e.g., at the level of a graduate-level introductory course).
The workshop will survey analytical techniques emerging from the intra-individual variability, multilevel modeling, dynamic systems, and machine learning perspectives, as well as address important factors related to research design and the collection of intensive longitudinal data.
Course materials include basic readings on the fundamental issues in the analysis of intensive longitudinal data, lecture notes, and a full set of R scripts. The course includes lectures on theory and construction of models for intensive longitudinal data along with lab sessions that examine how those models are specified, implemented in R, and fit to data. Participants are strongly encouraged to have their own data formatted and ready for analysis prior to the workshop.
Course instructors are Kevin J. Grimm, Department of Psychology at Arizona State University and Nilam Ram, Departments of Psychology and Communications at Stanford University.
- $600 for faculty ($300 for Cornell faculty)
- $300 for post-docs/graduate students ($150 for Cornell postdocs/grad students)
Kevin J. Grimm, Ph.D., is Professor of Psychology at Arizona State University where he teaches basic and advanced statistics courses including Longitudinal Growth Modeling, Data Mining in Psychology, and Structural Equation Modeling. He is an elected member of the Society of Multivariate Experimental Psychology and an Associate Editor of Structural Equation Modeling: A Multidisciplinary Journal. In 2017, he received the Cattell Award from the Society of Multivariate Experimental Psychology for outstanding early career contributions to multivariate experimental psychology. Dr. Grimm is the author of Growth Modeling: Structural Equation and Multilevel Modeling Approaches, with Nilam Ram and Ryne Estabrook, which was published by Guilford Press in 2017. He teaches workshops sponsored by the American Psychological Association’s Advanced Training Institute.
Nilam Ram, Ph.D., is a Professor in the Departments of Communication and Psychology at Stanford University. He serves on the editorial boards for the International Journal of Behavioral Development, Journal of Gerontology: Psychological Sciences, Psychology and Aging, and Research in Human Development and has served as a guest Editor for Research in Human Development and Psychology and Aging. He is an elected member of the Society of Multivariate Experimental Psychology. Dr. Ram has published over 2200 articles and chapters and is an author of Growth Modeling: Structural Equation and Multilevel Modeling Approaches along with Kevin J. Grimm and Ryne Estabrook. He teaches workshops sponsored by the American Psychological Association’s Advanced Training Institute.