# Analysis Core

> **NIH NIH P30** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2023 · $97,462

## Abstract

Abstract Analysis Core (AnC)
The Analysis Core will provide needed infrastructure for the training, research, and evaluation goals of the
CHECA project, especially the pilot research projects for the early-career investigators. The Analysis Core
members have a strong background in research design, sample size planning, exploratory and confirmatory
data analysis, and technical and academic writing. These tasks are expected to be done in dialogue and
collaboration with the researchers on the other cores, thus providing additional guidance and mentorship to
assist the early-career researchers in developing their awareness and skill in these areas. The Analysis Core
will also develop and disseminate training materials as needed.
An important Analysis Core mission will be assisting with the rigorous collection and management of evaluation
research data, and their analysis according to accepted statistical and methodological good practice, and their
adaptation where appropriate for sharing without violation of confidentiality. This will be especially relevant in
the development of behavioral intervention development training plans, which must combine substantive
knowledge of the research questions with sound statistical principles to draw appropriate conclusions.
Several themes are expected to be important in CHECA research, such as observational studies (including
questionnaires and longitudinal surveys) for identifying individual and community strengths and challenges,
and the evaluation of proposed interventions. Accordingly, a broad range of expertise is available for dealing
with these disparate design and analysis challenges.
Dr. Michael L. Berbaum, the head of the analysis core, has expertise in statistical analysis, writing and
administration and coordination of research as well as in the mentoring of early-career researchers. He has
extensive experience in research on racial and ethnic disparities on multiple health-related variables relevant to
cognition and life functioning. Dr. Tianxiu Wang is an experienced biostatistician and has collaborated
extensively on work related to cognitive decline and dementia in older adults. Dr. John J. Dziak has been a
lead or co-author on multiple conceptual or applied papers on topics related both longitudinal research, causal
inference, latent variable modeling, and intervention development and evaluation, including in clustered or
multilevel contexts. He has written tutorials on the practical interpretation of statistical results for substantive
researchers. Both Dr. Wang and Dr. Dziak are proficient in longitudinal data analysis, which is important for
research based on a life course perspective.
.

## Key facts

- **NIH application ID:** 10729953
- **Project number:** 1P30AG083255-01
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Michael Lawrence Berbaum
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $97,462
- **Award type:** 1
- **Project period:** 2023-08-15 → 2028-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10729953

## Citation

> US National Institutes of Health, RePORTER application 10729953, Analysis Core (1P30AG083255-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10729953. Licensed CC0.

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