Biostatistics and Analysis Analytics and statistics inform health risks for workers and other populations

The validity of the research study results hinges on the rigor of the design, quality of collected data and application of appropriate statistical methods to answer the research questions.

Fortified with many decades of experience, the Oak Ridge Institute for Science and Education plans and performs methodological assessments. These assessments are tailored to the specific issues of concern, and they produce relevant, reliable data. The defensible and insightful findings inform strategic planning and relevant decision making.

Why are biostatistics and analytics important?

ORISE supports ongoing programs involving medical surveillance of workers and other populations, as well as occupational epidemiology and research. ORISE also performs special analyses of health conditions and specific groups of workers, as required by the U.S. Department of Energy.

To ensure credibility and accuracy, all analyses are preceded by rigorous and thorough data collection, data cleaning and verification, and state-of-the-art data management processes. ORISE’s approach utilizes accepted and proven statistical processes, and when appropriate, adapts methods for novel applications. Results of analyses and interpretations of data findings are disseminated through clear and engaging reports, presentations, or online dashboards.

The experts at ORISE possess a range of capabilities essential for appropriate statistical analyses, including:

  • Study design and implementation
  • Records collection, computerization and evaluation of data for usability
  • Survey design and sampling
  • Data management, integration and verification
  • Design, implementation and evaluation of epidemiological surveillance programs
  • Power and sample size calculations
  • Descriptive data analysis including advanced data visualizations
  • Data modeling using parametric and non-parametric methods
  • Advanced methods for survival analyses, dose response and risk estimation
  • Interpretation and presentation of study results