Abstract:
Panel count data arise from longitudinal studies on recurrent events where each
subject is observed only at discrete time points. If recurrent events of several types are
possible, we obtain panel count data with multiple modes of recurrence. Such data is
commonly encountered in medical studies, reliability experiments as well as in sociological studies. In this article, we present cause specific rate functions for the analysis
of panel count data with multiple modes of recurrence and develop nonparametric estimation procedures for the same. We derive empirical estimators for the cause specific
rate functions and also propose a smoothed version of the same estimators using kernel
estimation method. Asymptotic properties of the proposed estimators are studied. A
simulation study is conducted to assess the performance of the proposed estimators in
finite samples. The practical utility of the proposed method is demonstrated using a
real life data arising from skin cancer chemo prevention trial given in Sun and Zhao
(2013).
