|(Tony) Jianguo Sun, University of Missouri, Columbia MO|
|Title: Regression Analysis of Longitudinal Data with Informative Observation Times and Application to Medical Cost Data|
Abstract: The analysis of longitudinal data with informative observation processes
has recently attracted a great deal of attention and some methods have been developed.
However, most of those methods treat the observation process as a recurrent event
process, which assumes that one observation can immediately follow another.
Sometimes, this is not the case, as there may be some delay or observation duration.
Such a process is often referred to as a recurrent episode process. One example
is the medical cost related to hospitalization, where each hospitalization
serves as a single observation. For the problem, we present a joint analysis
approach for regression analysis of both longitudinal and observation processes and
a simulation study is conducted that assesses the finite sample performance
of the approach. The asymptotic properties of the proposed estimates are also
given and the method is applied to the medical cost data that motivated this study.
Friday, Nov 8 at 2:00pm in Fretwell 205
Categories: Fall 2013