Comparison of cause specific rate functions of panel count data with multiple modes of recurrence

TL;DR

This paper introduces a nonparametric test for comparing cause-specific rate functions in panel count data with multiple recurrence modes, aiding analysis of complex recurrent event data.

Contribution

It proposes a novel nonparametric testing method for multiple recurrence modes in panel count data, with validation through simulations and real data applications.

Findings

The test performs well in finite samples.

It effectively distinguishes differences in cause-specific rates.

Application to real data demonstrates practical utility.

Abstract

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 for comparing cause specific rate functions of panel count data with more than one mode of recurrence. The test can also be employed to assess whether the competing modes of recurrence are affecting the recurrence times identically. 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.