Joel Dubin, University of California, Davis
Dynamical Correlation for Multivariate Longitudinal
Data
Longitudinal data with a single response are commonplace in
biostatistical studies. Some examples include monitoring blood
glucose levels over time for diabetes patients, evaluating tumor size
growth for cancer patients, checking CD4+ cell counts over time for
HIV positive patients, etc. A more difficult situation arises when
the responses over time are considered multivariate, where data on
several time courses are recorded per subject. We will discuss one
approach to handling this type of data from a study of hemodialysis
patients in which several acute phase blood proteins per patient were
measured longitudinally. In particular, we will present a
non-parametric method for describing the dynamical correlation between
multivariate longitudinal response curves, including consideration of
derivatives and time-shifted versions of curves.