Dr. Andrea Gottlieb (San Jose State University)

Title: A stickiness coefficient for longitudinal data

Abstract: The stickiness coefficient, a novel summary statistic for time-course and longitudinal data will be introduced. The stickiness coefficient provides a simple, intuitive and informative measure that captures key information contained in time-course data. Under the assumption that the data are generated by the trajectories of a smooth underlying stochastic process, the stickiness coefficient summarizes the extent to which deviations from the mean trajectory tend to co-vary over time.  The estimation scheme proposed will allow for estimation even in the case that the longitudinal data are sparsely observed at irregular times and may be corrupted by noise. The estimation procedure as well as consistency and convergence rates will be discussed.  I will illustrate the resulting stickiness coefficient with several theoretical calculations as well as economic and health related data examples.