SPONSORED RESEARCH: M4 Modules on Advanced Methodology when Modeling Multinational Data
December 15, 2025
Pictured Above: Aaron Kaat, PhD
Read a Q&A Below:
Aaron Kaat, PhD and the team at Northwestern University’s Feinberg School of Medicine Department of Medical Social Sciences (MSS) received an education-related grant from the National Institute on Aging titled: "M4 Modules on Advanced Methodology when Modeling Multinational Data." Co-investigators include Maxwell Mansolf, PhD, and Dan Mroczek, PhD, with additional program team members from the Outcome and Measurement Science and Determinants of Health divisions within MSS: Elizabeth Dworak, PhD, Eileen Graham, PhD, Catherine Han, PhD, Jing Luo, PhD, Stephanie Young, PhD, Katie Jackson, MS, and Manrui Zhang, PhD.
What are the aims of the project?
The prevalence of Alzheimer's disease and AD-Related Dementias (AD/ADRD) is increasing globally, highlighting an urgent need to identify factors influencing healthy aging and cognitive change. The Health and Retirement Study (HRS) and its sub-study—the Harmonized Cognitive Assessment Protocol (HCAP)—together with their international sister studies, provide invaluable resources for exploring the epidemiology of AD/ADRD. To equip the next generation of researchers with the necessary methodological skills to engage with these rich data in a meaningful way, we will develop “M4: Modules on Advanced Methodology when Modeling Multinational Data.”
Required modules will focus on the responsible conduct of secondary data analysis, social and behavioral factors related to AD/ADRD, reproducibility, and open science principles. Trainees will choose one or more optional advanced methodology modules appropriate for multinational analyses: item response theory (IRT), coordinated data analyses (CDA), or latent variable alignment methods. Each module will be taught across multiple sessions, allowing for didactic and hands-on training. We have four specific aims:
Aim 1 is to develop and refine a module-based training program in large-scale data analysis. This foundational step will involve creating the modules by leveraging and adapting our existing trainings and tutorials.
Aim 2 is to train participants in protective behavioral and social factors related to reducing AD/ADRD in cross-national contexts. Although many research questions can be explored using the HRS and HCAP, the core focus of this training is the study of AD/ADRD.
Aim 3 is to build open science resources that support identifying factors influencing the trajectory of healthy aging and AD/ADRD. We view open science as essential for expanding knowledge and ensuring reproducibility, particularly when working with widely available datasets such as HRS and HCAP.
Aim 4 is to provide ongoing mentorship in advanced methodologies. By engaging trainees across all modules, we can foster meaningful mentoring relationships and offer sustained support as they develop mastery in these advanced methods.
What are your next steps?
This is a 5-year project. This first year is focused on revising existing training materials to maximize applicability to the HRS and HCAP datasets, including their international sister projects. We are developing the modules for synchronous virtual learning sessions spread across multiple days throughout the year. This will allow participants to practice the skills that they are learning in between didactic sessions. In years two through five, we intend to offer the entire suite of modules on an annual basis. The long-term goal is to modify the content for asynchronous, self-paced learning for trainees interested in learning about the HRS and HCAP.
What do you hope will come out of this funded research?
The M4 project is unique, insofar as it is not designed to generate new knowledge—instead, it is an educational program intended to train other researchers in how to conduct secondary data analysis on cognitive and personality data related to cognitive aging. Because the trainings are offered virtually and the grant covers the program expenses, there is a low barrier for participation for potential trainees. Therefore, we hope to be able to reach a large number of trainees, including trainees from countries collecting data for HRS and HCAP sister projects. We hope to see many secondary research projects and publications coming out of the program participants in future years to maximize the impact!