Workshops

Tuesday, December 8, 2026  — 12 - 2:00 PM ET

Live via Zoom

Speaker: Dr. Claire Yang (Notre Dame)

Studies of time-related change are key to understanding the process and dynamics of aging but are often subject to data and methodological limitations associated with the confounding of different dimensions of time, including age (A), period (P), and cohort (C). The goal of this workshop is to introduce recent advances in data and analytic tools for modeling temporal variations due to A, P, and C effects in longitudinal analyses, teach the basic rationale and process of APC analysis, and give attendees a working knowledge of how to use this methodological approach in their own research on aging. The workshop builds on the previous GSA workshop on Coordinated Data Analysis (CDA) (2025) to provide useful guidelines for APC analysis based on both basic and complex longitudinal designs and data structures involved in CDA, which can vastly enhance analysts’ ability to make inferences about time-relate change compared to conventional studies of single datasets. The workshop provides an interactive virtual environment to facilitate active learning. It involves participation of attendees throughout the session, engaging them during the lecture and through breakout discussions as well as moderated Q&A for targeted problem solving.

Registration will take place via GSA (geron.org).

The Coordinated Data Analysis Workshop took place from Thursday, April 23 - Friday, April 24, 2026 at Northwestern University.

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CDA Training: During this two-day workshop led by Eileen Graham, attendees will be introduced to the rationale and process of coordinated data analysis. We will focus on the steps of CDA that are key to a successful project, including codebook organization, dataset censusing and selection, logical harmonization, preparation of statistical analysis scripts, and synthesis methods. Each component will include hands-on activities and materials that attendees can take back to their labs. Lastly, attendees will be broken into small groups to design and implement a small CDA which they will present at the end of the workshop. 

Attendee Selection Process: Please note, this is a data-intensive, hands-on workshop. Applicants should have prior experience with data management and statistical software(s). Advanced graduate students, postdocs, or faculty members are best suited to fully benefit from the sessions. Space for this workshop is limited.