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Biometrika 1992 79(3):513-522; doi:10.1093/biomet/79.3.513
© 1992 by Biometrika Trust
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Nonparametric tests of the Markov model for survival data

MICHAEL P. JONES1 and JOHN CROWLEY2

1Department of Preventive Medicine, University of Iowa Iowa City, Iowa 52242, U.S.A.
2Fred Hutchinson Cancer Research Center 1124 Columbia Street, Seattle, Washington 98104, USA.

Jones & Crowley (1989) introduced a general class of nonparametric statistics for right-censored survival data that includes many of the existing procedures involving a single covariate. This paper considers this class in the framework of a Markov model and suggests some tests especially appropriate for the Markov setting. Application to left-truncated and right-censored data is also given. Small sample properties and asymptotic relative efficiencies for several statistics of this class are investigated for both relative and excess risk models for the hazard.

Key Words: Censored data • Excess risk • Generalized log rank test • Kendall rank correlation • Markov model • Relative risk • Truncated data


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