http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/382 2026-04-20T13:52:38Z 2026-04-20T13:52:38Z Sankaran, P. G Ashlin Mathew P. M Sreedevi, E. P http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/418 2025-01-28T05:49:12Z 2024-11-01T00:00:00Z

Comparison of Cause Specific Rate Functions of Panel Count Data with Multiple Modes of Recurrence Sankaran, P. G; Ashlin Mathew P. M; Sreedevi, E. P Panel count data refer to the data arising from studies concerning recurrent events where study subjects are observed only at distinct time points. If these study subjects are exposed to recurrent events of several types, we obtain panel count data with multiple modes of recurrence. In the present paper, we propose a nonparametric test to compare cause specific rate functions of panel count data with more than one mode of recurrence. We carry out simulation studies to evaluate the performance of the test statistic in a finite sample setup. The proposed test is illustrated using two real-life panel count data sets, one arising from a medical follow-up study on skin cancer chemo prevention trial and the other on a warranty database for a fleet of automobiles.

2024-11-01T00:00:00Z Paduthol, Sankaran Mathew, Ashlin P M Sreedevi, E P http://starc.stthomas.ac.in:8080/xmlui/xmlui/handle/123456789/383 2025-01-17T05:24:03Z 2021-06-03T00:00:00Z

Cause specific rate functions for panel count data with multiple modes of recurrence Paduthol, Sankaran; Mathew, Ashlin P M; Sreedevi, E P 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).

2021-06-03T00:00:00Z