The Methodology Center at Purdue (MCAP) is now accepting applications for our NIH-supported Summer Institute on Longitudinal Data Analysis
Information for Participants
Our week-long Summer Institute on Longitudinal Data Analysis is designed to meet the needs of 50 participants each year, welcoming individuals from all career stages and backgrounds. We aim to support graduate students, post-docs, faculty, and industry researchers -- all of whom are eager to enhance their knowledge in longitudinal data analysis. Our Summer Institute will be held at Purdue University in West Lafayette, IN and we will provide meals and lodging in Purdue dorms for those selected to receive travel funding. The Summer Institute is ideal for individuals with a foundational understanding of statistics who seek to learn and apply longitudinal methods in their work. We specifically encourage applicants who are not already experts in longitudinal data analysis but who see the potential for these skills to enhance their research or professional contributions.
Applications are now open (see How to Apply section below). Applications will close on March, 15th, 2025.
When is the course? July 13th-July 18th, 2025
Where? Purdue University in West Lafayette, IN
How Much? $2,000 for the Registration Fee (see fee waiver information below)
In-Person Support:
With generous support from the National Institute on Drug Abuse (R25 DA061822), we are able to provide 30 participants with full support for living expenses, registration fee waivers, and travel costs. We aim for these funds to cover all costs of attending the summer institute.
Purdue-Affiliated Fee Waivers:
20 additional participants will be provided a waiver of registration fees to attend the summer institute free of cost. We expect these to be Purdue affiliated individuals and/or those local who do not require lodging or travel expenses.
Who Can Apply:
We encourage participants at any career stage to apply (e.g., graduate students, post-docs, faculty). We also encourage individuals from any health or social science discipline, or closely related field, to apply.
Learning Outcome Goals
- Expand interest and comfort applying longitudinal data to health and social science questions
- Increase understanding of mastery of longitudinal data and models, including developing skills to make justified measurement and modeling decisions
- Provide tools for data visualization for broad application of longitudinal analysis and dissemination of findings to interdisciplinary audiences
Featured Faculty
Dr. Kristine Marceau (MCAP Co-Director)
Dr. Marceau is an Associate Professor of Human Development and Family Science who specializes in longitudinal methods emphasizing both developmental change and variability across multiple time-scales using and integrating SEM and multilevel modeling techniques. She frequently uses family-based designs and large datasets to explore developmental and behavioral trajectories. Dr. Marceau regularly teaches multilevel modeling and inferential statistics, and trains students in longitudinal data analysis.
Dr. Trenton D. Mize (MCAP Co-Director)
Dr. Mize is the Dean's Associate Professor of Sociology and Statistics (by courtesy) and a quantitative methodologist with expertise in categorical data analysis, latent variable modeling, and data visualization. His research develops and applies innovative methods for analyzing complex social data, and he regularly teaches graduate courses on categorical data analysis, data visualization, and experimental design.
Dr. James A. McCann (MCAP Co-Director)
Dr. McCann is a Professor of Political Science with expertise in longitudinal survey analysis and latent variable modeling. He has led multiple large-N longitudinal studies on political behavior and representation and regularly applies advanced econometric and multilevel techniques in his research. Dr. McCann teaches graduate seminars on research design and quantitative analysis, focusing on panel data and survey methodologies.
Dr. Sharon Christ (MCAP Co-Director)
Dr. Christ is an Associate Professor of Human Development and Family Science specializing in emergent statistical models, particularly structural equation modeling (SEM) and complex sample designs. Her expertise in multilevel modeling, SEM, and growth models has been applied across numerous large-scale cohort studies. She has taught graduate-level courses on sample design, inferential statistics, and SEM.
Dr. Brian C. Kelly
Dr. Kelly is a Professor of Sociology at Indiana University with extensive experience using large national datasets and contextual indicators to examine health behaviors, particularly substance use. His NIH-funded research frequently integrates complex statistical models to assess the social contexts influencing health outcomes.
Dr. Robert Duncan
Dr. Duncan is an Assistant Professor of Human Development and Family Science at Colorado State University with expertise in advanced longitudinal data analysis, including multilevel modeling, structural equation modeling (SEM), and growth curve modeling. His work focuses on children’s development within multilevel contexts like classrooms.
Dr. Dongjuan Xu
Dr. Xu, an Associate Professor in the School of Nursing, specializes in longitudinal cohort studies that evaluate the quality of care and outcomes for older adults. Her expertise spans applied biostatistics, epidemiological methods, and outcome evaluation. She regularly teaches graduate courses in these areas, incorporating advanced quantitative techniques into her instruction, such as weighting methods and sampling designs.
Dr. Robbee Wedow
Dr. Wedow is an Assistant Professor of Sociology and Data Science at Purdue University, with expertise in statistical genetics and sociogenomics. His research applies advanced statistical methods, including gene-environment interaction models, to large-scale genetic datasets to investigate social and health outcomes.
How to Apply
We prioritize individuals based on their need for longitudinal methods training, and those with extensive experience in using large-scale longitudinal data may be rated as a lower priority for enrollment. Our application is now open and closes on March, 15th 2025. All applicants will be reviewed carefully to ensure they will benefit from the course content.
Ready to apply? Fill out an application at this link.