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Nonparametric Analysis of Recurrent Events and Death
Author(s) -
Ghosh Debashis,
Lin D. Y.
Publication year - 2000
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.2000.00554.x
Subject(s) - estimator , nonparametric statistics , mathematics , statistics , event (particle physics) , covariance , delta method , sample size determination , econometrics , physics , quantum mechanics
Summary. This article is concerned with the analysis of recurrent events in the presence of a terminal event such as death. We consider the mean frequency function, defined as the marginal mean of the cumulative number of recurrent events over time. A simple nonparametric estimator for this quantity is presented. It is shown that the estimator, properly normalized, converges weakly to a zero‐mean Gaussian process with an easily estimable covariance function. Nonparametric statistics for comparing two mean frequency functions and for combining data on recurrent events and death are also developed. The asymptotic null distributions of these statistics, together with consistent variance estimators, are derived. The small‐sample properties of the proposed estimators and test statistics are examined through simulation studies. An application to a cancer clinical trial is provided.