# Research Core 3: Analysis Core (RC3)

> **NIH NIH P30** · DUKE UNIVERSITY · 2022 · $291,304

## Abstract

PROJECT SUMMARY – Analysis Core (AC)
The Analysis Core supports the Duke OAIC effort to understand and optimize reserve and resilience by
providing data management and analytic support (Aim 1), providing methodological instruction (Aim 2), and
incorporating and developing innovative biostatistical analytic methodologies into the OAIC program (Aim 3).
The Analysis Core contains all the expertise needed to provide analytic support to junior and senior faculty
across the range of study designs and analytic issues, including biostatisticians with expertise in study design,
longitudinal analysis, psychometrics and estimation of latent variables; bioinformaticists with experience in
genetic and high dimensional data analysis; and day-to-day monitoring of studies and data management. Data
management will use secure web-based methods (REDCap) and methods for managing high dimensional
metabolomic, proteomic, and genetic data. Duke OAIC supported studies are constructed and managed so
that standardized analytic methods and common measures across studies can be employed. In addition to
provision of technical analytic and data management support, the Analysis Core will provide consultation and
training support to the faculty of the Duke OAIC (Aim 2). The Core will also pursue methodologic goals of
interest to biostatisticians advance statistical science and address analytic issues encountered in current
research (Aim 3). In particular, the study of resilience and reserve will require estimation of multi-parameter
models and latent classes. A Developmental Project is proposed to develop estimation models and assess
statistical performance (false detection rate, stability, power, bias, and validity) of these new classes of models.
Working closely with the Molecular Measures and Health and Mobility Measures Cores, the Analysis Core will
focus on methods for examining trajectories of change in the biological and clinical variables, develop
aggregation techniques for this high dimensional data, establish temporal ordering, assess mediation and
moderation pathways, and assess the statistical properties and constancy of the relationships across studies.

## Key facts

- **NIH application ID:** 10465210
- **Project number:** 5P30AG028716-17
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** CARL F PIEPER
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $291,304
- **Award type:** 5
- **Project period:** 2006-09-15 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10465210

## Citation

> US National Institutes of Health, RePORTER application 10465210, Research Core 3: Analysis Core (RC3) (5P30AG028716-17). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10465210. Licensed CC0.

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