BSU Seminar

Speaker: Professor Michael Elliott, University of Michigan School of Public Health - Michael Elliott - Faculty Profiles - U-M School of Public Health

Abstract: Longitudinal data has become a major part of the landscape for clinical and epidemiological research.  While variance is typically understood as nuisance – the “noise” in “signal-to-noise” – there is increasing evidence that underlying variability in subject-level measures over time may also be important in predicting future health outcomes of interest. However, most statistical methods development has been focused on the use of mean trends obtained from longitudinal data; approaches that incorporate subject-level variability are far rarer, and consequently use of such information is rare.  I will provide a review of several methods developed to incorporate variability of predictors in a range of statistical modeling settings, including using repeated cognitive testing to assess risk of dementia onset, hormone profiles to assess health outcomes in menopausal women, and heart rate data to assess stress in racially discriminatory settings.

This will be a free hybrid seminar. To register to attend remotely, please click here: https://cam-ac-uk.zoom.us/meeting/register/2QnjjKu5RK2BaGy1Hgq7mQ