A class of multi-sample nonparametric tests for panel count data |
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Authors: | N Balakrishnan Xingqiu Zhao |
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Institution: | (1) Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada, N2L 3G1; |
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Abstract: | This paper considers the problem of multi-sample nonparametric
comparison of mean functions of point processes with panel count
data, which arise naturally when recurrent events are considered.
Such data frequently occur in medical follow-up studies and
reliability experiments, for example. For the problem considered, we
construct a class of nonparametric test statistics based on the
integrated weighted differences between the estimated mean functions
of the point processes. The asymptotic distributions of the proposed
statistics are rigorously derived when the monotonicity assumptions
for weight processes are removed, and their finite-sample
properties are examined through Monte Carlo simulations. The
simulation results show that the proposed methods are good for
practical use and are slightly powerful than the existing tests. A
set of panel count data from a cancer study is analyzed and
presented as an illustrative example. |
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Keywords: | |
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