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A Class of $K$-Sample Tests for Comparing the Cumulative Incidence of a Competing Risk

The Annals of Statistics · 1988 · Vol. 16(3)

Abstract

In this paper, for right censored competing risks data, a class of tests developed for comparing the cumulative incidence of a particular type of failure among different groups. The tests are based on comparing weighted averages of the hazards of the subdistribution for the failure type of interest. Asymptotic results are derived by expressing the statistics in terms of counting processes and using martingale central limit theory. It is proposed that weight functions very similar to those for the $G^p$ tests from ordinary survival analysis be used. Simulation results indicate that the asymptotic distributions provide adequate approximations in moderate sized samples.

Statistical Distribution Estimation and ApplicationsStatistical Methods and InferenceStatistical Methods and Bayesian InferenceMathematicsStatisticsMartingale (probability theory)Cumulative incidenceAsymptotic analysisSample size determinationEconometricsApplied mathematics
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References
Nonparametric Inference for a Family of Counting Processes
The Annals of Statistics · 1978 · 1,473 citations
The Statistical Analysis of Failure Time Data.
Biometrics · 1981 · 9,990 citations
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