Join TraCS to better understand the necessary vocabulary and fundamental concepts used to communicate with biostatisticians. Come and get a fresh introduction to statistical terms, methodologies and analysis strategies most commonly used in clinical/translational research.

This introduction will also include an overview of:

• Basic study designs used in clinical/translational research
• Statistical methodology definitions and examples
• Analysis strategies: Which statistical methods are appropriate for various types of data?

The course will also include two sessions in which participants will discuss peer-reviewed literature and learn to evaluate the choice of study design and analysis plan.

The webinar link will be emailed to you upon registration.

Presented by:
Marcella Boynton, PhD, Adjunct Assistant Professor
Department of Health Behavior, Gillings School of Public Health

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NIH is committed to advancing research and its data science efforts to end the COVID-19 pandemic. As part of the larger NIH COVID-19 response, NIH leadership is designing a COVID-19 Clinical Data Hub – a loosely federated system, built by researchers for researchers, to quickly make available the data necessary to address pressing COVID-19 research questions.

The primary goals of this workshop are to:

• Review existing platforms within the NIH and how they approach COVID-19 use cases.
• Discuss the challenges and approaches to data harmonization, data source linkage, private/public data, and social determinants of health.
• Understand the challenges and approaches to data tracing, appropriate representation, and avoiding selection bias.
• Consider governance, internal review boards, data access committees, eligibility, and confidentiality in data use.
• Understand the global and societal impact of COVID-19 research.
• Develop an approach to data ingestion and harmonization that will position the NIH for success against the COVID-19 pandemic.

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