Presenter: Alexander Y. Mitrophanov, PhD, Senior Statistician, ABCS/FNLCR (Frederick, MD)

When several statistical tests are performed, simultaneous use of the resultant “raw” (i.e., test-generated) P-values can lead to an increased overall false-positive rate. To keep that rate under control, various statistical procedures have been developed. These procedures, generally known as P-value adjustment strategies, are the main subject of this lecture. We will review the conceptual foundation behind P-value adjustment, take a closer look at some common adjustment strategies, and see how P-value adjustment can be performed in practical situations relevant to biomedical research. Beginner level of statistical knowledge is expected, intermediate is preferred. Familiarity with previous “Statistics for Lunch” lectures on P-values is also strongly encouraged.

This will be a hybrid event. Please register at this link.

This session will be recorded, and materials will be shared with attendees a few days after the event.

For additional details and questions, please contact Natasha Pacheco (natasha.pacheco@nih.gov), Advanced Biomedical Computational Science group, Frederick National Laboratory for Cancer Research.