Nonparametric Analysis of Recurrent Events and Death

2000/06/01 by Debashis Ghosh, D. Y. Lin · 30 citations
Mathematics · Computer Science · #Statistical Methods and Inference #Statistical Methods in Clinical Trials #Bayesian Methods and Mixture Models

paper · doi:10.1111/j.0006-341x.2000.00554.x

Abstract

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.

Citations

• Weighted Kaplan-Meier Statistics: A Class of Distance Tests for Censored Survival Data

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