# Statistics Core

> **NIH NIH P01** · ALBERT EINSTEIN COLLEGE OF MEDICINE · 2024 · $635,559

## Abstract

ABSTRACT
The Statistics Core (SC) serves as the statistical support hub of the Einstein Aging Study (EAS). A primary
scientific goal of this Core is to advance our understanding of how individual in-depth characterization of health
behaviors, biomarkers, physical and psychosocial health, and environmental factors impact cognitive
performance and decline prior to onset of Alzheimer’s disease and related dementias and assessing the role of
multiple exposures that influence cognition on a short-term and long-term basis. To achieve this goal, the EAS
collects data across multiple timescales ranging from real-time to annual assessments, combining conventional
in-person interviews, self-reports and clinical assessments with data streams from wearables (e.g., actigraphy
for measurement of sleep and physical activity, air quality monitors, continuous glucose monitors – CGM) and
collected via mobile devices (e.g., ecological momentary assessment (EMA) surveys and ambulatory cognitive
assessments). The SC will continue in its long history of developing and applying cutting-edge analytic
approaches to address the research questions described in the four scientific Projects and to assist in service
to the other Cores. It serves two functions that are essential for the success of EAS. First, the SC will provide
collaborative and consultative support to Project investigators for data analyses and interpretation of results.
Second, the SC will engage in methodological development to meet the challenges posed from complications
encountered in analyses and study design. The SC team plays a key role in assisting EAS investigators with all
stages of data analysis, such as tailoring analysis plans to specific scientific hypotheses, conducting data
analysis, interpreting results, and addressing challenges and potential threats to validity. In particular, the SC
will work closely with the Technology and Data Management Core to insure data quality. In short, the SC will
continue its long history of contributions to aging research through developing new statistical methodology and
through innovative application of existing methodologies.

## Key facts

- **NIH application ID:** 10857292
- **Project number:** 5P01AG003949-40
- **Recipient organization:** ALBERT EINSTEIN COLLEGE OF MEDICINE
- **Principal Investigator:** Cuiling Wang
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $635,559
- **Award type:** 5
- **Project period:** 1982-09-29 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10857292

## Citation

> US National Institutes of Health, RePORTER application 10857292, Statistics Core (5P01AG003949-40). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10857292. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*