  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
chemoprevention trial given in Sun and Zhao (2013).
