The Biostatistics, Epidemiology, and Research Design (BERD) Program

Your resource for research design support and consulting services from health data experts.

Supported through the FSU-UF Clinical and Translational Science Award

Click here for information on Health Data Access.

The BERD Program provides a central location to access support services related to human health data and research including:

  • Clinical research design
  • Biomedical informatics database access (e.g., OneFlorida Data Trust)
  • Quantitative and qualitative analysis
  • Access to support services for health data collection (e.g., REDCap)

We link investigators with multidisciplinary faculty members and experts in various methodological techniques including biostatistics, epidemiology, biomedical informatics, artificial intelligence, qualitative research, and measurement and evaluation in health-related research. Investigators can consult with the BERD team for research design, data acquisition and management, and data analysis needs that are applicable across the entire spectrum of clinical and translational research.

Vision: To equip translational scientists with new capabilities to answer questions that cannot be answered today. These capabilities will be enabled by new data sources and types both at the Florida State University­–University of Florida CTSA Hub and statewide. We anticipate that FSU researchers, from students to faculty, will use these new capabilities to conduct priority studies that aim to improve healthcare outcomes.

We provide one-on-one consultations as needed, and particularly early in the design stage. Please utilize the BERD Consulting Suite ticketing system to request assistance. See below for more information on services.

In addition, we have a BERD Canvas site that contains informatics training resources and information about the OneFlorida Data Trust, including publications, i2b2 query examples, and a recording of the OneFlorida i2b2 workshop held April 1, 2020. Enroll in the Canvas site, and enjoy the resources and workshops!

The main goals of BERD are to:

  1. Align resources throughout FSU through collaborations among but not limited to FSU’s Innovation Hub, School of Information (iSchool), University Libraries, College of Medicine, and departments of Statistics and Scientific Computing. 
  2. Offer training workshops in core data analytic skills including data acquisition, data cleaning, data analytics software (e.g., SAS, SPSS, R, and Python), data mining, machine learning, and data visualization.
  3. Provide health data portals for accessing resources, including the OneFlorida Data Trust.
  4. Develop a catalog of health-related data sources and investigator needs.
  5. Provide training and access to health data query, collection, and storage capabilities including i2b2, Qualtrics, and REDCap.
  6. Provide easy access to consultants through the BERD Consulting Suite. Investigators and students can submit service requests through the ticketing system:
  7. Clinical research support services are provided by the FSU Network for Clinical Research and Training, and include protocol review, regulatory support, and other research services. The NCRT home page contains information about services provided. Investigators, coordinators, and students can request services through the NCRT Support Request Form. General questions may be directed to


Henry J. Carretta, PhD, MPH
Assistant Professor, Behavioral Sciences and Social Medicine, College of Medicine
I am a health services epidemiologist and research methodologist. I apply methods and conceptual models from public health, health economics, and health services research using domains of equity, effectiveness, and efficiency. My research focus is on the interrelationship between individuals’ characteristics, the residential community in which they are embedded, and the medical care system as it relates to persons and populations with chronic conditions in the United States. I use secondary data analysis to address research questions using state and national administrative data (e.g., claims, discharge abstracts, and electronic health records) and national health surveys (e.g., the CDC’s Behavioral Risk Factor Surveillance System and the National Survey of Children with Special Health Care Needs).

Hongyuan Cao, PhD
Associate Professor, Statistics, College of Arts and Sciences
My research interests and expertise include high dimensional and large scale statistical analysis, survival analysis, longitudinal data analysis, and biostatistics and bioinformatics. More specifically, I develop statistical methods for large and complex data for statistical applications in social, biological, and medical sciences. Big data revolutionized many scientific disciplines and requires domain knowledge and statistical and computational tools for good interpretation. My work can provide such tools. Moreover, partnerships with substantive experts not only helps them to use the right statistical model but also synergizes my development of statistical methods.

Grant MacDonnell, MS
Director of Medical Informatics Research, College of Medicine
My background is in computational biology with a focus on evolution. For the better part of the last decade, I have developed medical informatics solutions to aid researchers. The solutions I can develop range from simple database development to development and implementation of machine learning algorithms and even mobile apps.

Zhe He, PhD
Associate Professor, School of Information, College of Communication and Information
Core Affiliate, Institute for Successful Longevity
My research lies in biomedical and health informatics, machine learning, clinical research informatics, knowledge representation, and data analytics. My overarching goal is to improve population health and advance biomedical research through the collection, analysis, and application of electronic health data from heterogeneous sources. I received have two distinguished paper awards from the American Medical Informatics Association. My research has been funded by the National Institutes of Health, Eli Lilly and Company, Amazon, NVIDIA, and FSU’s Institute for Successful Longevity.

Lifeng Lin, PhD
Assistant Professor, Statistics, College of Arts and Sciences
My research interests include applications of Bayesian methods to medical and clinical data, efficient and robust methods for meta-analyses and systematic reviews, methods for addressing publication and related bias, and multivariate and network meta-analyses of multiple outcomes and multiple treatments. My work has been published in top statistical, epidemiological, and medical journals, including Biometrics, BMJ, Epidemiology, Journal of Clinical Epidemiology, and Journal of Statistical Software.

BERD Consulting Suite

Through the Biostatistics, Epidemiology, and Research Design (BERD) Consulting Suite, faculty, students, and residents can, with advance registration, have a biostatistics, epidemiology, informatics, and research design consultation with a BERD expert. These consultations are limited in scope and are intended to help researchers understand the underlying statistical aspects of their research design so that they can adequately plan projects.

Those who use the BERD Consulting Suite can get personalized advice on:

Statistical Analysis Design                                                          Biomedical Informatics Planning

  • Interpretation of statistical results
  • Simple sample size and statistical power calculations
  • Analyzing data
  • Appropriate statistical software
  • Appropriate selection of statistical tests
  • Setting up a dataset for analysis
  • Designing informatics and AI approaches for research projects
  • Natural language processing
  • Machine learning / Deep learning 
  • Data management using REDCap / Unity
  • Data safety and HIPAA
  • Project management


RDDC Services:

University of Florida Research Design and Data Coordinating Center (RDDC) provides the following services to FSU researchers:

Study Design and Grant Proposal Development: RDDC supports traditional design (parallel group design, cross-over design, factorial design, randomized consent design, group sequential design), adaptive design (sample size, study duration, allocation probabilities, drop/add treatment arms, subgroup enrichment), and other designs (micro-randomized designs with individual and dynamic tailoring, platform trials with multiple interventions at one platform, pragmatic trials).

Statistical Data Analysis: RDDC supports analyzable data preparation, statistical modeling and inference, and results interpretation.

Data Management and Secure Data Sharing: RDDC supports electronic data capture, study monitoring, and data analysis. RDDC also helps investigators develop and apply technologies for privacy-preserving data collection and analysis. 

Data Collection and Data Cleaning: RDDC supports data quality check, data collection, and data cleaning

All the service requests from FSU researchers shall still be submitted first to FSU BERD ticketing system at We will triage your tickets to UF RDDC if needed. 

Last Updated: Wednesday, June 30, 2021 at 9:15 AM