Biostatistics & Quantitative Shared Resource (BQS SR) Division of Quantitative Sciences
The University of Florida Health Cancer Center (UFHCC) Biostatistics & Quantitative Sciences Shared Resource (BQS SR) provides biostatistical leadership and analytic collaborative support to members of the UFHCC.
Through this support, the BQS SR plays a critical role in clinical trials; population-based studies, including epidemiologic, health outcomes/behavior, and health disparities research in our catchment area; molecular biology studies, including genome sequencing for translational research and experimental therapeutic studies; and laboratory-based research.
Services are provided as a no chargeback system and provides support for short and moderate term projects free of charge along with the development of research projects. Services include:
- Conceptualization of a research project, including development of research questions and hypotheses.
- Study design, including sample size justification/power analysis; analytical planning.
- Basic data management, including guidance in the development of study databases, the establishment of procedures for monitoring data quality, and the preparation of analysis datasets.
- Statistical analyses and interpretation of results for collected data.
- Assistance in grant writing.
- Assistance in manuscript writing.
- Development of statistical methods, tools, or computer programs that are required to conduct studies, if appropriate approaches are not currently available.
- Short courses covering basic biostatistics for cancer researchers.
For the names and contact information UFHCC Division of Quantitative Sciences members and expertise, click here.
To request support, click here.
Ji-Hyun Lee, DrPH
Division of Quantitative Sciences
University of Florida Health Cancer Center;
Professor, Department of Biostatistics
University of Florida
Office Phone: 352-273-9079
Office Phone: 352-273-7137
Cancer and Genetics Research Complex
2033 Mowry Road
Gainesville, FL 32610
- NIH Guidance: Scientific rigor and transparency
- Training Modules to Enhance Data Reproducibility
- Nature: Statistics for Biologists