# Core B: Analytics Core

> **NIH NIH P01** · BOSTON UNIVERSITY MEDICAL CAMPUS · 2024 · $618,906

## Abstract

ANALYTICS CORE SUMMARY
The Analytics Core will support all four research components of the TIME-AD program, ensuring coordinated
statistical approaches and principled decisions on common challenges. The Analytics Core will (1) work with
the Cognition, Exposure, and Covariates Core to ensure construction of analytic data sets is consistent with
each proposed study design for each research project; (2) partner with research project leads to develop and
implement the analytic strategy for each research project, develop template analysis code for each method,
and lead program-wide methodologic decisions; (3) guide investigative teams in each research project on
systematic evidence triangulation across study designs; (4) and provide ad hoc guidance on statistical
problems that arise in each research project. The TIME-AD program proposes to implement combinations of
multiple analyses of AD/ADRD risk factors, relying on different assumptions for causal identification. Methods
include doubly robust g-estimation methods using covariate adjustment; instrumental variables analyses
drawing on policy or genetic instruments; bias-detecting Mendelian Randomization; and quantitative bias
analysis. These approaches will be complemented by methods to quantify the total effect of interventions on
each risk factor on population incidence of AD/ADRD and inequalities in AD/ADRD. Population impact
assessments will include population attributable fraction calculations and effect estimate transport methods
that allow estimation of total effects in populations with different risk factor profiles. The team includes
researchers with expertise in each of these methods. The TIME-AD program uses data from multiple sources,
including population-representative cohorts with regularly scheduled measurement waves (Health and
Retirement Study, National Longitudinal Study of Youth 1979, Reasons for Geographic and Racial Disparities
in Stroke, National Health and Aging Trends Study) and cohorts relying on convenience (UK Biobank, All of
US) or membership-based (Kaiser Permanente Northern California) based samples with electronic health
record follow-ups. Together these data sets provide excellent statistical power to deliver precise estimates and
evaluate effects in racial/ethnic and socioeconomic subgroups. The different data sources best support
different study designs, and each entails specific methodologic challenges. The Analytics Core will ensure a
unified framework, foster reproducible research and high-quality implementation, and make it feasible to tackle
these multiple designs with multiple data sets in each study. The Analytics Core will also work closely with the
Equity and Dissemination Core to ensure analytic decisions reflect the TIME-AD goal of delivering evidence
with the best chance to reduce AD/ADRD inequities and identify drivers of AD/ADRD in communities
historically underrepresented in AD/ADRD research. The Analytics Core will guarantee integration of the
project...

## Key facts

- **NIH application ID:** 10934710
- **Project number:** 1P01AG082653-01A1
- **Recipient organization:** BOSTON UNIVERSITY MEDICAL CAMPUS
- **Principal Investigator:** Chiung-Yu Huang
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $618,906
- **Award type:** 1
- **Project period:** 2024-09-15 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10934710

## Citation

> US National Institutes of Health, RePORTER application 10934710, Core B: Analytics Core (1P01AG082653-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10934710. Licensed CC0.

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