# Core C -- Statistics Core

> **NIH NIH U19** · UNIVERSITY OF WISCONSIN-MADISON · 2022 · $291,388

## Abstract

ABSTRACT – STATISTICS CORE
The Core’s overarching goal is to provide methodological and statistical support for all research projects in the
U19 and Adjunct AD/ADRD U01, and facilitate the use of the rich MIDUS longitudinal data to the fullest extent
possible by investigators. Core activities encourage the development of innovative, integrative cross-project
studies, building on the strong interdisciplinary team of scientists and substantive aims shared by MIDUS
projects. Core services will complement and enhance the public use MIDUS data so that it provides the
greatest value-added to the larger scientific community. The centerpiece of the Core is the provision of multiple
workshops, involving invited experts, project investigators, and users of the publicly available data, to examine
integrative pathways using complex methods and shared measures, targeted toward fully exploiting the multi-
wave, multi-cohort MIDUS survey data, and its novel genetic, biomarker and neuroimaging data. Specifically,
the Core will (1) Promote maximal use of complex multi-faceted MIDUS longitudinal data. The Statistics Core
will organize workshops focused on relevant methodological and data analytic issues addressing four themes:
(a) advanced statistical methods that exploit the longitudinal data to address study aims; (b) the use and
analysis of new genetic, biomarker, and neuroscience data; (c) analytic challenges shared across the projects
(e.g., missing data techniques such as multiple imputation); and (d) substantive and conceptual challenges
that unify the projects (e.g., conceptualization, analysis, and modeling age-period-and cohort effects).
Selection of specific topics is an ongoing and iterative process, designed to meet the evolving needs of the
MIDUS investigators and user community. (2) Facilitate cross-study science. The Statistics Core will facilitate
and guide cross-study comparisons with other major longitudinal studies. The Core leaders will demonstrate
how to carry out multi-study comparisons and advise data users on the best ways to deploy MIDUS in such
integrative analyses. We will borrow the tools of meta-analysis to use MIDUS within multi-study frameworks.
We will also use and advise data users on methodologies such as random effect meta-analysis, which permit
the consideration of study-level variables to explain differences among findings. (3) Provide analytic guidance
in analysis of historical context effects. The Stats Core will provide illustrative guidance and statistical
consultation on data analyses that exploit opportunities afforded by the MIDUS design to examine long-term
impacts of the Great Recession, and more recently, impacts of the COVID-19 pandemic on the physical,
psychological, economic, and social well-being of MIDUS participants. The objective is to assist investigators
with analyses that compare outcomes before and after the Great Recession and the COVID-19 pandemic, both
offering natural experimental designs of within-per...

## Key facts

- **NIH application ID:** 10559175
- **Project number:** 2U19AG051426-06A1
- **Recipient organization:** UNIVERSITY OF WISCONSIN-MADISON
- **Principal Investigator:** CAROL D. RYFF
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $291,388
- **Award type:** 2
- **Project period:** 2016-07-25 → 2028-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10559175

## Citation

> US National Institutes of Health, RePORTER application 10559175, Core C -- Statistics Core (2U19AG051426-06A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10559175. Licensed CC0.

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