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Data Management and Analysis Core

work desk with laptop, spreadsheets, small succulents and coffee cup

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

DMAC Services

Click on the + symbols below to learn more about the services we offer.

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 services 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 services include:

  • 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
screenshot of UNC COVID-19 dashboard
Featured Work

FPG's Data Management and Analysis Core (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.

Zadrozny saw the benefit of partnering to provide support for methodology, data management, and analysis to develop better tools to aid decision-making and the public health response to COVID-19.

"As fast as the information is changing, collaborative relationships are the only way that we can efficiently learn incrementally more about how SARS-COV-2 is transmitted, which control measures work effectively, and whether school districts can effectively enforce control measures to safely engage in face-to-face instruction," says Zadrozny.


DMAC Leadership
Sabrina Zadrozny smiling at camera

Director, Data Management and Analysis Core

Rose Byrnes smiling at camera

Deputy Director (Interim), Data Management and Analysis Core

DMAC Staff

Adam Mack, Applications Analyst
Amber Robb, Workflow Architect
Brianne Tomaszewski, Research Assistant Professor
Dave Gardner, Applications Specialist
David Bogojevich, Research Assistant
Emma Tzioumis, Teaching Assistant Professor
Eric Savage, Applications Analyst
Jim Peak, Applications Specialist
Joy Yin, Applications Specialist Programmer
Keil Jones, Applications Specialist Programmer
Laura Kuhn, Advanced Research Scientist
Sarah Wackerhagen, Research Associate
Steve Magers, Applications Specialist
Tom Leggett, Applications Analyst
Gabrielle Jenkins, Graduate Research Assistant
Kylie Bezdek, Graduate Research Assistant
Tiffany Foster, Graduate Research Assistant