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This talk considers approaches to analysis of data from longitudinal research projects where pandemic onset occurred mid study. Once data are collected, the goals are to diagnose whether pandemic onset impacted study results and, if so, which types of effect estimates are affected. Given the diagnostic information, investigators can choose which effect estimates to report, i.e., pooled-data, pre-pandemic, and/or pandemic-era estimates. This is an expansion and improvement of a similar talk I gave as part of a CAPS Roundtable in November 2020 and includes some revised recommendations.
Presenter: Steve Gregorich, PhD - UCSF DOM, Division of General Internal Medicine
Steve Gregorich is a statistician focused on clinic- and community-based health disparities research in the areas of cancer prevention and survivorship, smoking cessation, women's health, oral health, HIV prevention, and language barriers in clinical care. Via the UCSF Center for Aging in Diverse Communities (CADC), he provides research mentorship to junior faculty who are committed to careers focused on reducing and eliminating health disparities.
Hosted by UCSF Center for AIDS Prevention Studies (CAPS) Methods Core