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Data Management and Analysis Core

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The Data Management and Analysis Core (DMAC) provides support for interdisciplinary child development research. Support services include proposal development, specific aims, study design, sampling, data collection, participant recruitment, data management, data visualization, and statistical analysis for projects ranging from small pilot studies, secondary data analysis, longitudinal cohorts, and large-scale multi-site cluster randomized controlled trials. We currently support more than 20 projects and have served as a data coordinating center, data management hub, and methodologic support for projects for more than 30 years.

To learn more, please email: FPGdata@unc.edu

DMAC Services

Click on the + symbols below to learn more about the support we offer. Contact us at FPGdata@unc.edu.

New Project and Proposals

  • Study methods consultation
  • Study design consultation
  • Proposal development, writing, and refinement
  • Full critical proposal review

Study Design

We provide study design support for a variety of study types, including: longitudinal, cross-sectional, nested cohort study designs, randomized controlled trials, cluster randomized controlled trials, secondary data analysis plans, nested cohort studies, and bio-behavioral approaches (e.g., two-stage studies, case cohort, case control studies).

Our study design support includes:

  • Formulating aims and hypotheses
  • Writing and editing analysis plans
  • Sample selection methods
  • Power and sample size calculations
  • Protocol development
  • Randomization strategies

Electronic Data Collection

  • Electronic informed consent capture
  • In-person data collection (via Blaise, REDCap) of assessments, interviews, biomarkers data, etc. with built-in scripts, validation, adaptive sequencing, and data integrity monitoring tools
  • Web-survey (via custom system, Qualtrics, REDCap) including automated mailings and incentive distribution
  • Cleaning, double entry, and reconciliation of paper-based data collection

Study Tracking

  • Participant and study activity tracking from recruitment through closure
  • Basic: support setting up tracking in Excel or Access database
  • Complex: custom interactive web-based systems that integrate participant information, study activity tracking, data files received, reporting, and alerts

Data Management

  • Database development
  • Data cleaning, error checking and reconciliation, and field staff
  • Harmonization of variables across time points, versions, and variable changes
  • Scoring standardized assessment instruments
  • Validation
  • Data conversion/formatting (e.g., NDAR/ECHO)
  • Cohort building
  • Data linkage (i.e., building secondary datasets from multiple/varied sources)
  • Auditing data/variables (i.e., quality assurance)

Data Analysis

  • Descriptive data
  • Simple GIS analysis
  • SEM
  • Cluster randomized controlled analysis
  • Hierarchical linear regression
  • Time-to-event analysis (survival analysis)
  • Marginal structural models
  • Longitudinal data analysis
  • Missing data assessment and methods
  • Population/sampling weights
  • Inverse probability weights
  • Intent to treat analyses (ITT)
  • Treatment on the treated (ToT)

Data Sharing, Visualization, and Dissemination

  • Secure data sharing and receiving, coordinating across sites, de-identification of data, and uploading to registries
  • Preparation of figures, tables, and graphic representations for presentations and publications
  • Writing methods, results, and discussion sections of reports and manuscripts
  • Interactive website for data visualization (e.g., Tableau, R/Shiny)

To engage any of the above support, email us at: FPGdata@unc.edu

screenshot of UNC COVID-19 dashboard
Featured Work

In 2021, DMAC partnered with the Department of Epidemiology at the UNC Gillings School of Global Public Health to coordinate the UNC Gillings COVID-19 Dashboard. The dashboard's goal is to make more resources and data visualizations available for different audiences, including the general public, as well as providing a specific kind of guidance for COVID-19 researchers and policymakers. DMAC Director Sabrina Zadrozny, Eric Savage, Adam Mack, and David Bogojevich all worked on this project.


sabrina zadrozny; woman with short dark hair smiles at camera
DMAC Leadership

Sabrina Zadrozny, PhD, is director of the Data Management and Analysis Core and a statistician investigator at FPG. She is an interdisciplinary epidemiologist, with training in longitudinal research methods, causal inference, infectious disease epidemiology, and reproductive, pediatric, and perinatal epidemiology.

Contact her:


DMAC Staff

Jim Peak, Applications Specialist
Joy Yin, Applications Specialist Programmer
Keil Jones, Applications Specialist Programmer
Laura Kuhn, Advanced Research Scientist
Nupur Mishra, Applications Analyst
Ping Chen, Social Science Research Methodologist
Steve Magers, Applications Specialist
Tom Leggett, Applications Analyst

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